{"id":"W6929829503","doi":"10.5067/c18gqdvvrhoy","title":"SMAPVEX16 Manitoba Surface Roughness Data, Version 1","year":2018,"lang":"en","type":"dataset","venue":"Earth Observing System Data and Information System","topic":"Infectious Diseases and Tuberculosis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Surface roughness; Surface finish; Surface (topology); Deformation (meteorology); Noise (video)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006454579,0.002723884,0.00115745,0.003143576,0.0007548792,0.00103598,0.0028866,0.001493749,0.01606557],"category_scores_gemma":[0.002457642,0.0006912361,0.00141977,0.004675629,0.0004282656,0.0007028184,0.001214556,0.001392842,0.03538487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001458444,"about_ca_system_score_gemma":0.0038095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1529357,"about_ca_topic_score_gemma":0.241082,"domain_scores_codex":[0.9995153,0.0000669681,0.00004741273,0.0001273962,0.0001331784,0.0001096713],"domain_scores_gemma":[0.9990588,0.0000909936,0.00006657444,0.0002299215,0.0004302304,0.000123496],"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":[0.0001461132,0.00006563693,0.003025614,0.0003643369,0.00005941169,0.00004572492,0.00004581327,0.0009739401,0.0003805764,0.0001797186,0.9899424,0.004770542],"study_design_scores_gemma":[0.0005126843,0.00006343561,0.04054165,0.0003376289,0.00009409214,0.0001500938,0.0003137036,0.004271436,0.001497536,0.0008380947,0.9512958,0.0000839112],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001228612,0.00007319958,0.00009546834,0.00005679095,0.00003522238,0.000022972,0.9973323,0.0006493528,0.0005060612],"genre_scores_gemma":[0.0008502803,0.00003984262,0.0002286666,0.00001458483,0.000006152327,0.00005429516,0.9981592,0.00003868203,0.0006081804],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8470643,"threshold_uncertainty_score":0.3040911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234044628994134,"score_gpt":0.2596179118975493,"score_spread":0.2272774656076079,"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."}}