{"id":"W4406432091","doi":"10.1016/s0765-2046(97)80143-8","title":"10.1016/s0765-2046(97)80143-8","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Genomics; Gerontology; Functional genomics; Library science; Medicine; Biology; Genetics; Computer science; Genome; Gene","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00196166,0.004834292,0.003480731,0.003965019,0.003459308,0.006246221,0.005221844,0.007249138,0.9905879],"category_scores_gemma":[0.002592068,0.001558938,0.002321295,0.004275055,0.003215816,0.00809432,0.005414149,0.004507259,0.9959096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001732483,"about_ca_system_score_gemma":0.001533024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004823334,"about_ca_topic_score_gemma":0.00379687,"domain_scores_codex":[0.9989091,0.00006724205,0.00008931382,0.0004194162,0.0002758171,0.0002391505],"domain_scores_gemma":[0.9962741,0.000935021,0.0002679386,0.000508384,0.000789219,0.001225416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004751728,0.0002527508,0.0007520366,0.0006233086,0.00005357244,0.0002071774,0.0001144748,0.0005414072,0.002049919,0.00556535,0.4090281,0.5803367],"study_design_scores_gemma":[0.00008775412,0.0001265474,0.000713923,0.0004055582,0.00002089673,0.0003069979,0.0001259982,0.0003096159,0.0003957262,0.0008000192,0.996669,0.00003801201],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00043524,0.0004612706,0.0009137297,0.0005592691,0.0004282182,0.0001559105,0.001217582,0.001934064,0.9938948],"genre_scores_gemma":[0.0004378909,0.0002232008,0.0004864708,0.0003014336,0.00008605138,0.0001054865,0.0006293088,0.0003156714,0.9974145],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.00941205,"threshold_uncertainty_score":0.01342505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008901069603388805,"score_gpt":0.221182971415853,"score_spread":0.2122819018124642,"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."}}