{"id":"W2389483589","doi":"","title":"Stability Analysis for Elementary Characters of Hybrid Rice by AMMI Model","year":2002,"lang":"en","type":"article","venue":"Zuo wu xue bao","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Ammi; Adaptability; Stability (learning theory); Mathematics; Yield (engineering); Main effect; Grain yield; Interaction; Linear regression; Gene–environment interaction; Statistics; Horticulture; Biology; Genotype; Computer science; Ecology; Genetics; Machine learning","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":[0.002671682,0.001066441,0.0006069596,0.001313315,0.0003917756,0.0006675292,0.000514991,0.0003087337,0.001691699],"category_scores_gemma":[0.005477739,0.000233972,0.001102499,0.0009236914,0.0003940484,0.0008098608,0.0005246641,0.000763012,0.0005841795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004610735,"about_ca_system_score_gemma":0.0003125029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00128773,"about_ca_topic_score_gemma":0.0006732739,"domain_scores_codex":[0.998779,0.0005048536,0.00006922695,0.0003015579,0.0002557246,0.0000896311],"domain_scores_gemma":[0.9981396,0.00107098,0.0002361306,0.0002213753,0.0002811125,0.00005082681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002355557,0.0004593372,0.1391138,0.0003884924,0.001142543,0.0005314825,0.001593425,0.3424809,0.2139247,0.02398414,0.003637294,0.2703883],"study_design_scores_gemma":[0.00003570707,0.0003945858,0.072069,0.00001265838,0.0001294812,0.0002592334,0.0001143936,0.898925,0.01898386,0.006826049,0.002141612,0.0001083968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4500003,0.0001993048,0.5459103,0.00008751785,0.00003425184,0.00007798592,0.0005597417,0.0009971736,0.002133383],"genre_scores_gemma":[0.9329218,0.00008830416,0.06354331,0.00001286026,0.00001505431,0.0002195007,0.001220872,0.0002103033,0.001768078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002671682,"threshold_uncertainty_score":0.0141294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02931364038405715,"score_gpt":0.2044416335223243,"score_spread":0.1751279931382672,"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."}}