{"id":"W4393889122","doi":"10.5281/zenodo.8154672","title":"BioDeepTime: database and compilation code","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Database; Computer science; Code (set theory); Programming language","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008183943,0.0002248662,0.0001935764,0.0002592643,0.00128989,0.0005104225,0.0009872352,0.0002798856,0.001104127],"category_scores_gemma":[0.001146647,0.0002259683,0.00005602682,0.0002810982,0.0004544341,0.00001219674,0.002750016,0.0003575602,0.01061877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003717641,"about_ca_system_score_gemma":0.00001258459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003362046,"about_ca_topic_score_gemma":0.000005270706,"domain_scores_codex":[0.9979824,0.000203911,0.0003378456,0.0005259547,0.0005134307,0.0004364854],"domain_scores_gemma":[0.9983899,0.0000189863,0.0001350609,0.0007440874,0.0004090531,0.0003029316],"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":[0.00005047441,0.00005851762,3.631546e-7,0.0002374882,0.00005595036,0.000006836504,0.0000294967,0.000003213531,0.00384639,0.00001065983,0.9836468,0.01205386],"study_design_scores_gemma":[0.0004146533,0.0003754691,0.00007440896,0.00004719375,0.00002445747,0.00004513533,0.00007897135,0.0001710067,0.0004473253,0.00001943758,0.9980516,0.0002503596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003403082,0.0001788243,0.0006080213,0.0003240489,0.0001645075,0.0004246527,0.9962212,0.0001277024,0.001610686],"genre_scores_gemma":[0.0002064709,0.003469571,0.0001922213,0.0001595632,0.0003426451,9.460441e-8,0.9943203,0.0005238377,0.0007853376],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01440484,"threshold_uncertainty_score":0.999809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03806320532596763,"score_gpt":0.280869321928475,"score_spread":0.2428061166025074,"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."}}