{"id":"W6907947199","doi":"10.25545/6dgf1v/cueqbf","title":"3_DSLR.JPG","year":2024,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Identification (biology); Natural (archaeology); Product (mathematics); Work (physics)","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000197742,0.0003324442,0.0002144361,0.0001139809,0.00005860757,0.00009341865,0.0007378801,0.0004946869,0.001624007],"category_scores_gemma":[0.0002410096,0.0003048764,0.0001242745,0.0001012331,0.00008930325,0.000003866026,0.0009067676,0.0005390535,0.02954402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002088306,"about_ca_system_score_gemma":0.0001386972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006899343,"about_ca_topic_score_gemma":0.0001201119,"domain_scores_codex":[0.998716,0.00003577598,0.0002999094,0.0004305241,0.0002240475,0.000293744],"domain_scores_gemma":[0.9982079,0.00001165635,0.0001316073,0.001507859,0.00003884673,0.0001021358],"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":[0.00001493217,0.0000218906,0.000005235271,0.0002352015,0.00009899236,0.00003021731,0.000006284666,0.00001614866,0.0001280144,0.000008616071,0.9991717,0.0002627962],"study_design_scores_gemma":[0.0001600458,0.0001207088,0.000002624637,0.00006014653,0.0001091584,0.0000473478,0.00001881553,0.0000734917,0.0001423237,0.00001229691,0.9988989,0.0003541048],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004532594,0.0001040429,0.00004254897,0.00003485729,0.001014144,0.0001568069,0.9968374,0.00003055968,0.001734319],"genre_scores_gemma":[0.000009467005,0.0005787003,0.0006135121,0.0006615753,0.0007738837,0.00001127239,0.9942415,0.00003302998,0.003077105],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02792001,"threshold_uncertainty_score":0.9999403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005661468393171776,"score_gpt":0.2597627303322914,"score_spread":0.2541012619391196,"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."}}