{"id":"W3166881399","doi":"10.1002/agj2.20765","title":"Predictions of soybean harvest index evolution and evapotranspiration using STICS crop model","year":2021,"lang":"en","type":"article","venue":"Agronomy Journal","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Evapotranspiration; DSSAT; Cultivar; Leaf area index; Agronomy; Crop; Mathematics; Environmental science; Parametrization (atmospheric modeling); Crop coefficient; Yield (engineering); Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001018389,0.00005548007,0.00006913955,0.000009905569,0.0002307291,0.0000624829,0.00003916625,0.00004832804,0.00005296184],"category_scores_gemma":[0.00001704948,0.00002677522,0.00003798516,0.0001145196,0.00003373705,0.00015449,0.00001351809,0.00008454997,4.292229e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002981636,"about_ca_system_score_gemma":0.00003810165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002517037,"about_ca_topic_score_gemma":0.00008517616,"domain_scores_codex":[0.9994879,0.00003220033,0.00018446,0.00009265478,0.0001110674,0.0000917456],"domain_scores_gemma":[0.9996229,0.00001846825,0.00009941775,0.00002178053,0.0001805841,0.00005685944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002008083,0.0001446513,0.1164638,0.000009807923,0.00004660077,0.00000269413,0.0002970925,0.06193161,0.7962857,0.001393397,0.0001541849,0.02325032],"study_design_scores_gemma":[0.0003009819,0.0001059198,0.654623,0.00005327897,0.00005604351,0.00008338599,0.0005193888,0.3325248,0.005909077,0.005434994,0.0002423504,0.0001467891],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599666,0.0002358693,0.03939106,0.0001508154,0.00006943818,0.0000393085,0.0000113722,0.000005544724,0.0001299778],"genre_scores_gemma":[0.9982809,0.00003140249,0.001439488,0.00002092701,0.0001489948,7.700472e-7,0.00001410324,5.79992e-7,0.0000628609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7903767,"threshold_uncertainty_score":0.1774605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402423257679713,"score_gpt":0.2289397428838485,"score_spread":0.1949155103070513,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}