{"id":"W4386417962","doi":"10.3390/ani13172793","title":"Reliability Associated with the Measurement of Continuous Variables in Veterinary Medicine: What the Different Possible Indicators Tell, and How to Use and Report Them","year":2023,"lang":"en","type":"article","venue":"Animals","topic":"Veterinary Practice and Education Studies","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Reliability (semiconductor); Cornerstone; Reliability engineering; Variable (mathematics); Gold standard (test); Medicine; Field (mathematics); Statistics; Computer science; Veterinary medicine; Mathematics; Engineering; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.003688802,0.000118084,0.0002853924,0.0000710477,0.0004244836,0.0000329559,0.00009233932,0.00005786172,0.00002228022],"category_scores_gemma":[0.002760077,0.00005361916,0.00001344151,0.0004142931,0.0001624387,0.0002277019,0.0001800584,0.0002229447,0.000003074184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005854772,"about_ca_system_score_gemma":0.00007876145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002670826,"about_ca_topic_score_gemma":0.0001175805,"domain_scores_codex":[0.9983125,0.0006196938,0.0002881831,0.0002286588,0.0003109,0.0002400804],"domain_scores_gemma":[0.9965714,0.002573761,0.0003080508,0.0002967014,0.0001939789,0.0000561198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003044182,0.00007863349,0.9472692,0.0001283285,0.0001217547,0.00003413482,0.03286443,5.843345e-7,0.003128071,0.00009218366,0.01531196,0.0006663133],"study_design_scores_gemma":[0.000281142,0.0004266724,0.9281626,0.0004388397,0.00004467607,0.00001069249,0.06256276,0.000003207472,0.00001915055,0.00008280609,0.007905167,0.00006227989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702765,0.0002547074,0.000001836451,0.02838444,0.0001340266,0.0007035247,0.000003960344,0.00002697508,0.0002139884],"genre_scores_gemma":[0.9980493,0.0008754344,0.00001487491,0.0005125063,0.00003305851,0.0001878891,0.000002679616,0.00001083318,0.0003134348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02969833,"threshold_uncertainty_score":0.3304269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.274803084058999,"score_gpt":0.4191453590143812,"score_spread":0.1443422749553822,"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."}}