{"id":"W6931758559","doi":"10.5683/sp2/vagk02","title":"Okotoks Erratic -- Okotoks -- Laser Scanning -- Metadata -- 2016","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Metadata; Laser scanning; Laser; Point cloud; Cloud computing","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":[0.001599129,0.0008710404,0.0008072749,0.0001852853,0.0005393444,0.0002459022,0.001622488,0.0006229109,0.008662724],"category_scores_gemma":[0.0004956377,0.0008113869,0.0002144258,0.0003111897,0.0008962955,0.0008666206,0.001416573,0.0009933978,0.003396464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007287329,"about_ca_system_score_gemma":0.0001413732,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08621308,"about_ca_topic_score_gemma":0.02784687,"domain_scores_codex":[0.9940894,0.0005022542,0.0008802101,0.001906376,0.001304575,0.001317141],"domain_scores_gemma":[0.9955698,0.0002401507,0.0006169032,0.002908596,0.00002044717,0.0006440592],"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":[0.0000177844,0.0001011795,0.0001754809,0.00006769849,0.00007644434,0.0001026568,0.00007681653,0.00001788296,0.00004092091,0.000001368212,0.9976229,0.001698874],"study_design_scores_gemma":[0.0004138877,0.0001212146,0.003502283,0.0002162486,0.0002588654,0.00002651681,0.00004889745,0.0000648616,0.0001955695,0.0001404385,0.9941115,0.0008997423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002183587,0.00009680408,0.0002373142,0.0003237489,0.0003339229,0.001139613,0.9906788,0.00009561201,0.006875788],"genre_scores_gemma":[0.00008944201,0.0004929773,0.0007376289,0.003434123,0.0006196134,0.0002537087,0.9922589,0.0001138103,0.001999774],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05836622,"threshold_uncertainty_score":0.9994337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02200372963565396,"score_gpt":0.2733316998216918,"score_spread":0.2513279701860378,"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."}}