{"id":"W4398563650","doi":"10.7910/dvn/apacse/veogzc","title":"SER38 AEV W-E 50K IRREGULAR.tab","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Art","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":[0.000210232,0.0006141826,0.0005816249,0.0002863571,0.00007361384,0.000166631,0.001381971,0.0005137228,0.007727773],"category_scores_gemma":[0.0001253015,0.000685139,0.0001495868,0.0004211955,0.00007554588,0.0001883081,0.0005810103,0.001581859,0.3670845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002074236,"about_ca_system_score_gemma":0.00008232015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005496108,"about_ca_topic_score_gemma":0.00002494046,"domain_scores_codex":[0.9975111,0.00003544842,0.0003936322,0.0006025207,0.0006981412,0.0007591818],"domain_scores_gemma":[0.9975063,0.00008364533,0.00004623042,0.001884128,0.00004196945,0.0004377366],"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":[0.00001086727,0.00001774992,3.137505e-7,0.001010306,0.0001807161,0.0003202951,0.00001385968,0.005948041,0.0003012725,0.00001877256,0.9919029,0.0002748381],"study_design_scores_gemma":[0.0003486947,0.00002213219,0.000007566192,0.00009850895,0.00008206475,0.00002290987,0.00001572026,0.004003012,0.0002847155,0.000008047368,0.9944416,0.0006649991],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000008613158,0.000007678897,0.000499245,0.000007045043,0.001196967,0.0003657489,0.9965696,0.0008158405,0.0005292183],"genre_scores_gemma":[0.00003358517,0.0007938208,0.0008780934,0.00008428244,0.001045317,0.00008356584,0.9967292,0.0001594022,0.0001927315],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3593567,"threshold_uncertainty_score":0.99956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01237238966325708,"score_gpt":0.2189764042880246,"score_spread":0.2066040146247675,"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."}}