{"id":"W6923397905","doi":"10.1371/journal.pone.0172918.g001","title":"Genetic and phenotypic trends in CHD.","year":2017,"lang":"en","type":"other","venue":"Figshare","topic":"Education Methods and Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Labrador Retriever; Genetic data; Shetland; German; Selection (genetic algorithm); Population","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":[0.0002554113,0.00008896522,0.00007729905,0.001259691,0.0001640363,0.0002164631,0.0001633845,0.000220168,0.009710302],"category_scores_gemma":[0.0009600152,0.00006787703,0.0001867769,0.001359635,0.0001127267,0.0002154834,0.000172251,0.00025891,0.0007676965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001851982,"about_ca_system_score_gemma":0.0001620427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01496004,"about_ca_topic_score_gemma":0.02115425,"domain_scores_codex":[0.9998704,0.0000264871,0.00001167044,0.00003657005,0.00002936371,0.00002548698],"domain_scores_gemma":[0.9995645,0.00008260049,0.0001267952,0.00003389905,0.0001052844,0.00008693994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003007793,0.00005297938,0.9704754,0.00002784274,0.00007022014,0.0002212313,0.0001582321,0.0001708251,0.001180987,0.0002649742,0.003765147,0.02331143],"study_design_scores_gemma":[0.000001987426,0.00002588961,0.9990962,0.000005289039,0.000008413059,0.0001520316,0.00006671549,0.00007657873,0.00003834076,0.00003275689,0.0004941152,0.000001699835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794844,0.0004680203,0.0003503298,0.0002400969,0.00003544758,0.00001345272,0.01157396,0.0000538337,0.007780414],"genre_scores_gemma":[0.9893557,0.0002835064,0.0004977527,0.00003214174,0.00002898886,0.00001344331,0.006817734,0.00002830591,0.002942351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01496004,"threshold_uncertainty_score":0.03248423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126037134582512,"score_gpt":0.4115489695799013,"score_spread":0.2989452561216501,"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."}}