{"id":"W4293198497","doi":"","title":"Water activity - An efficient tool for seed testing","year":2009,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec)","funders":"","keywords":"Environmental science; Agricultural engineering; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009497871,0.0008776726,0.000473971,0.001880241,0.0003387509,0.0006382868,0.0007147214,0.0007407163,0.005779043],"category_scores_gemma":[0.001098986,0.0004419909,0.0004017527,0.0011331,0.0003739152,0.0008592207,0.0007736341,0.0007362342,0.004312261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002183418,"about_ca_system_score_gemma":0.000271128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004872725,"about_ca_topic_score_gemma":0.0009184522,"domain_scores_codex":[0.9983095,0.0002511655,0.00009661302,0.0003343983,0.000919295,0.00008897608],"domain_scores_gemma":[0.9993481,0.0001733187,0.00008803466,0.00009891879,0.0002492502,0.00004238998],"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":[0.00008842395,0.00005804783,0.001851554,0.0003634486,0.00001821645,0.0001630465,0.0000926038,0.0002791948,0.9347594,0.0005781353,0.001037877,0.06071002],"study_design_scores_gemma":[0.000009358378,0.0002438336,0.004235861,0.0000705355,0.00003925476,0.0004889494,0.00008521936,0.003991088,0.9661191,0.0004456971,0.02424354,0.00002757743],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2360205,0.01912249,0.6829975,0.0007972113,0.0006809928,0.001573876,0.005536288,0.008897904,0.04437315],"genre_scores_gemma":[0.6237379,0.008836218,0.3173226,0.000449801,0.0001231764,0.001651784,0.003258603,0.001022108,0.04359774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005779043,"threshold_uncertainty_score":0.01933289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941995313040924,"score_gpt":0.2284792820185386,"score_spread":0.1990593288881294,"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."}}