{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001052994,0.00377685,0.002280971,0.003369515,0.001187582,0.00354232,0.005123714,0.002416539,0.1938207],"category_scores_gemma":[0.003558949,0.00130123,0.001836502,0.004773589,0.0006605243,0.002306695,0.003481496,0.002368875,0.3495909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001129533,"about_ca_system_score_gemma":0.001896914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01666852,"about_ca_topic_score_gemma":0.02900884,"domain_scores_codex":[0.9987414,0.0001758656,0.00009611215,0.0004337346,0.0002967014,0.0002561845],"domain_scores_gemma":[0.9987198,0.0001848869,0.0000799205,0.0004916939,0.000329099,0.0001946698],"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":[0.00004762918,0.00001694443,0.0001638892,0.000219076,0.00001648505,0.000009074613,0.00001214624,0.0001105024,0.0001709614,0.0002537374,0.9972472,0.001732378],"study_design_scores_gemma":[0.0001950744,0.00002068475,0.0009216865,0.00007943324,0.00001965758,0.00004051705,0.00005568026,0.0005165565,0.0008723149,0.001043476,0.996208,0.00002683649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001619682,0.00005385413,0.0001965493,0.00006373873,0.00003895996,0.00002096323,0.993014,0.004678206,0.00177184],"genre_scores_gemma":[0.0003492739,0.00003328325,0.000482755,0.00004699643,0.000008720926,0.00005631493,0.9970052,0.0006555082,0.001361887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8061793,"threshold_uncertainty_score":0,"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."}}