{"id":"W4390681341","doi":"10.52269/22266070_2023_1_132","title":"YIELD AND FEATURES DETERMINING PRODUCT QUALITY IN SAMPLES OF ALFALFA COLLECTION","year":2023,"lang":"en","type":"article","venue":"3i intellect idea innovation - интеллект идея инновация","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sowing; Yield (engineering); Geography; Agronomy; Horticulture; Forestry; Biology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004385927,0.0004246898,0.000338798,0.002508944,0.0005832751,0.0008203639,0.0002208387,0.0002733633,0.001119457],"category_scores_gemma":[0.0007110666,0.0001557631,0.0004485178,0.002602169,0.0002835612,0.0003155124,0.0003101524,0.0002426781,0.0005347533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005212156,"about_ca_system_score_gemma":0.0001805637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004076899,"about_ca_topic_score_gemma":0.006726687,"domain_scores_codex":[0.9994571,0.00004007525,0.00004933855,0.0001544144,0.0002392874,0.00005987909],"domain_scores_gemma":[0.9993533,0.00005824852,0.0001422312,0.00003978793,0.000346267,0.00006008412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001722598,0.0001766236,0.5147631,0.0002732855,0.0002288019,0.0006782969,0.00133322,0.0004642199,0.4436312,0.0001542028,0.0003546456,0.03621975],"study_design_scores_gemma":[0.000006000401,0.0004139276,0.9638937,0.000012684,0.00009517466,0.0004061659,0.0006319107,0.0002571648,0.03215329,0.00005041314,0.002066189,0.00001345427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954147,0.0004256696,0.001011008,0.000008067806,0.000006647577,0.00002460914,0.001494923,0.00002867231,0.001585733],"genre_scores_gemma":[0.9918697,0.0002432433,0.002114983,0.00001559905,0.000008709082,0.00003529214,0.004150957,0.00003212246,0.001529428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004076899,"threshold_uncertainty_score":0.008106351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0859812035389117,"score_gpt":0.2904069511052751,"score_spread":0.2044257475663634,"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."}}