{"id":"W4390398287","doi":"10.30835/2413-7510.2023.293891","title":"Залежність інтенсивності наливу зерна та вологовіддачі від цінних господарських ознак кукурудзи","year":2023,"lang":"en","type":"article","venue":"Plant Breeding and Seed Production","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ripeness; Ripening; Moisture; Water content; Horticulture; Agronomy; Biology; Environmental science; Materials science; Composite material; Geology","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":[0.0004329661,0.0002529672,0.0003297026,0.0009636896,0.000590736,0.001277771,0.0002542458,0.0003504952,0.008152022],"category_scores_gemma":[0.0005924685,0.0003365884,0.0002924256,0.001111669,0.000749114,0.0005537099,0.0003900457,0.0006308423,0.0029759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147181,"about_ca_system_score_gemma":0.0006182206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0018556,"about_ca_topic_score_gemma":0.0032126,"domain_scores_codex":[0.9994963,0.00004816507,0.00002569514,0.0001406065,0.0002141165,0.00007502597],"domain_scores_gemma":[0.9996101,0.00005600217,0.0001181631,0.00005056509,0.0001201999,0.00004483495],"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":[0.0005536044,0.0001530444,0.02576793,0.0005828654,0.00005759672,0.001524055,0.001263239,0.00155783,0.7236881,0.02158654,0.001683866,0.2215813],"study_design_scores_gemma":[0.00007933374,0.001140859,0.2495392,0.0002591144,0.0001871862,0.005353573,0.002422297,0.0041158,0.4619331,0.02120457,0.2534801,0.0002848063],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8336587,0.01744918,0.0702097,0.0005765095,0.0002826434,0.0002091562,0.001920952,0.0003703351,0.07532289],"genre_scores_gemma":[0.9501445,0.004045988,0.02860078,0.00007712855,0.00007938661,0.0001404373,0.0007487296,0.000118678,0.01604431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008152022,"threshold_uncertainty_score":0.02727121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0333636814603233,"score_gpt":0.1933919290936091,"score_spread":0.1600282476332858,"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."}}