{"id":"W2387928040","doi":"","title":"Breeding and High Yield Cultural Technology of Nice No.1","year":2010,"lang":"en","type":"article","venue":"Seed","topic":"Flowering Plant Growth and Cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Nice; Yield (engineering); Agronomy; Biology; Computer science; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0004844765,0.0005225863,0.000728414,0.001232161,0.001115205,0.0005433821,0.0006308537,0.0004613208,0.002467799],"category_scores_gemma":[0.0003123069,0.0003071036,0.001130122,0.0006235981,0.000329073,0.0002141022,0.0007107818,0.0008770554,0.001697039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006510535,"about_ca_system_score_gemma":0.0007907177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004328826,"about_ca_topic_score_gemma":0.008900706,"domain_scores_codex":[0.999527,0.00006636931,0.00002827237,0.0001263233,0.0001940842,0.00005802365],"domain_scores_gemma":[0.9997177,0.00003408856,0.00002929669,0.00005576441,0.00008021112,0.00008289814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001738847,0.00006408799,0.002774142,0.0001888911,0.00002203327,0.0003050547,0.0002946473,0.0006367591,0.958187,0.001421155,0.001243018,0.03468946],"study_design_scores_gemma":[0.0001705366,0.002019323,0.1258142,0.0001222211,0.0004125391,0.007029308,0.0003219112,0.00626594,0.6471817,0.001464999,0.2089488,0.0002484784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8319973,0.003761858,0.1102894,0.0007993357,0.0002959608,0.0004488278,0.002436798,0.001664883,0.04830547],"genre_scores_gemma":[0.7386905,0.002614944,0.1814335,0.0002359219,0.0001484525,0.0004928357,0.008538869,0.0007207323,0.06712419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004328826,"threshold_uncertainty_score":0.008607268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009572847548261437,"score_gpt":0.1858967646334923,"score_spread":0.1763239170852309,"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."}}