Core Entities
- Crop — plant asset being analyzed.
- Parameter — growth/handling variable (light, EC, pH, stress, harvest timing).
- Nutrient — measured compound or antinutrient outcome.
- Claim — extracted directional statement tied to a source span.
Glass Biome · AI-native research infrastructure
91 cultivars across 13 verticals. AI scans agricultural research papers, extracts cultivar × parameter × nutrient × outcome findings, and validates them at the USDA-ARS lab on campus. Each cycle adds to the database.
S.01 The Engine
Live view of the evidence base: papers ingested, claims extracted, and connections discovered. Scans run against Europe PMC, Semantic Scholar, and OpenAlex with Unpaywall full-text enrichment.
Pipeline health at a glance: papers ingested, claims extracted, links discovered, and extraction yield rates.
Distribution of evidence across crops, parameters, and nutrients. Identifies where the strongest signals are and where coverage gaps remain.
Cell intensity = claim count for each crop-nutrient pair. Hover for details.
Red cells = zero evidence for this crop-nutrient pair across the full ontology.
Aggregated crop × parameter × nutrient relationships. Each row summarizes all claims for a triple into a dominant direction and mean confidence — the basis for dose-response models and protocol recommendations.
| Crop | Parameter | Nutrient | Claims | Direction | Confidence |
|---|
Extraction quality metrics. Direction indicates whether a parameter increases, decreases, or has nonlinear effects on a nutrient. Confidence reflects extraction certainty, not statistical significance.
Nutrient pairs and triads that respond to the same growing parameters within a crop — potential shared metabolic pathways. Higher scores indicate stronger co-occurrence across multiple independent studies.
Nutrients ranked by research priority: human deficiency prevalence weighted against available evidence depth. High-priority gaps are where growing protocols could have the most impact on public health outcomes.
Pre-LLM structural links: dose-response fits, hidden nutrient synergies, and third-order triads. These are computed from co-occurrence and ontology rules — causal validation requires Opus extraction.
| Crop | Parameter | Nutrient | Model | Strength | Direction | N | Mean Effect % |
|---|
| Crop | Nutrient Pair | Relationship | Bioavail. Score | Deficiency Adj. | Claims | Note |
|---|
| Crop | Nutrient Triplet | Anchor | Triad Score | Hypothesis |
|---|
First-principles pathway predictions: the inference engine maps (crop × parameter × nutrient) triples through KEGG pathways and signal mappings to predict nutrient directions without relying on empirical claims. Unconfirmed predictions are novel hypotheses warranting experimental validation.
| Crop | Parameter | Nutrient | Predicted Direction | Confidence | Category | Pathways |
|---|