{"id":"W6959202820","doi":"10.6084/m9.figshare.c.3726184_d5","title":"Additional file 5: Table S3. of Genetic mapping of principal components of canine pelvic morphology","year":2017,"lang":"en","type":"article","venue":"Figshare","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Principal component analysis; Table (database); Labrador Retriever; Base (topology); Genome; Gene mapping","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001452052,0.001500653,0.001895226,0.003015822,0.001402085,0.00163941,0.002550217,0.001019265,0.8564916],"category_scores_gemma":[0.02200596,0.0007982845,0.00117373,0.004946505,0.0003588245,0.001381706,0.0009392666,0.00112587,0.149397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008804968,"about_ca_system_score_gemma":0.00170504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01834226,"about_ca_topic_score_gemma":0.02848292,"domain_scores_codex":[0.9992687,0.0001367883,0.0001018127,0.0002406773,0.0001341238,0.0001178807],"domain_scores_gemma":[0.9842775,0.01235378,0.0006219202,0.0009713251,0.001305214,0.0004701906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004406933,0.000160357,0.00876051,0.002562403,0.0001464263,0.0002333815,0.0001464174,0.0007792078,0.0003784579,0.0006955336,0.9742069,0.01148976],"study_design_scores_gemma":[0.009056536,0.000523435,0.1247156,0.004780321,0.0008558889,0.001953806,0.001603973,0.005808564,0.002906118,0.01421309,0.8331728,0.0004098861],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003063038,0.00001320853,0.0003379833,0.00004630038,0.00002124599,0.00004814611,0.998535,0.0002081284,0.000483722],"genre_scores_gemma":[0.01049477,0.0001266357,0.004654006,0.0003577455,0.00007178105,0.00127369,0.9739302,0.001124211,0.007966862],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8564916,"threshold_uncertainty_score":0.2046973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06287484788366075,"score_gpt":0.2284972060392402,"score_spread":0.1656223581555794,"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."}}