{"id":"W6995375752","doi":"","title":"U.F.O. Ontario","year":2017,"lang":"en","type":"other","venue":"YorkSpace (York University)","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Work (physics); Government (linguistics); Natural (archaeology); Identification (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000238868,0.0002352484,0.0002312795,0.0003054831,0.00009302708,0.00005951112,0.0004465852,0.000395618,0.002638509],"category_scores_gemma":[0.000005868581,0.0002925401,0.00008533731,0.0001297056,0.00005163051,0.00004862804,0.00004401887,0.0003247297,0.0005165222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002357767,"about_ca_system_score_gemma":0.00008636562,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004737257,"about_ca_topic_score_gemma":0.06775925,"domain_scores_codex":[0.9993981,0.00001082388,0.00004471919,0.0002107721,0.0001150192,0.0002205681],"domain_scores_gemma":[0.9992903,0.000009539542,0.00007183627,0.0004997549,0.00001394391,0.0001146294],"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":[0.000002966448,0.000008495385,0.0001002664,0.00003061758,0.0001344142,0.00007881636,0.0001666376,0.005234051,5.932735e-7,0.0003509889,0.9922587,0.001633472],"study_design_scores_gemma":[0.0002667506,0.000006280503,0.00001333618,0.0001694549,0.00004830626,0.000001948099,0.00007350303,0.001418981,0.000003661892,0.000002431105,0.9976708,0.0003246002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000005327903,0.00048098,0.01390363,0.0000237222,0.001142883,0.00009665235,0.00001521476,0.001128207,0.9832034],"genre_scores_gemma":[0.00003989931,0.000305232,0.02246729,0.000009445675,0.0002087745,2.790696e-7,0.00003429037,0.0002456998,0.9766891],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.063022,"threshold_uncertainty_score":0.9999527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0104292921465821,"score_gpt":0.1709481520243232,"score_spread":0.1605188598777411,"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."}}