{"id":"W4290734813","doi":"10.2312/3dor.20181053","title":"SHREC 2018 - Protein shape retrieval","year":2018,"lang":"","type":"article","venue":"Espace ÉTS (ETS)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Information retrieval; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001489091,0.000732441,0.0005952524,0.0002396164,0.0005332268,0.0003286856,0.001311384,0.001309143,0.002403854],"category_scores_gemma":[0.001789352,0.0006766862,0.0003784891,0.0006212641,0.002413634,0.00002305476,0.001239635,0.0006875779,0.003442632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001254528,"about_ca_system_score_gemma":0.001113782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004361978,"about_ca_topic_score_gemma":0.0001396551,"domain_scores_codex":[0.9943513,0.000266213,0.0009721899,0.001159043,0.001397289,0.00185394],"domain_scores_gemma":[0.9960587,0.00004664155,0.0003682593,0.001555712,0.0008281248,0.001142538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002884968,0.0007599285,0.0005598486,0.0006594681,0.0005357208,0.00004519264,0.001178987,0.000001589165,0.7735185,0.0001957479,0.1300514,0.08960857],"study_design_scores_gemma":[0.001428342,0.003521087,0.000588114,0.0001659446,0.00005346364,0.00002397514,0.0003938514,0.001859909,0.3857983,0.000119207,0.6052682,0.0007795797],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414625,0.005065509,0.002445986,0.01051191,0.003472912,0.002773674,0.0003185858,0.00008532761,0.03386362],"genre_scores_gemma":[0.9435759,0.002186736,0.003593164,0.001040618,0.005018889,0.0000285858,0.0002024122,0.0001088375,0.04424485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4752167,"threshold_uncertainty_score":0.9999874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715989133811315,"score_gpt":0.2852715340724541,"score_spread":0.268111642734341,"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."}}