{"id":"W4313461148","doi":"10.54846/jshap/1300","title":"Maximizing value and minimizing waste in clinical trials in swine: Selecting outcomes to build an evidence base","year":2023,"lang":"en","type":"article","venue":"Journal of Swine Health and Production","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"University of Guelph","keywords":"Outcome (game theory); Clinical trial; Consistency (knowledge bases); Intervention (counseling); Medicine; Intensive care medicine; Computer science; Internal medicine; Nursing; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.795907,0.003491319,0.01142925,0.02585412,0.003345989,0.01771444,0.004768524,0.01020439,0.002462229],"category_scores_gemma":[0.841772,0.002983087,0.006674471,0.01580285,0.009420755,0.01639136,0.01274529,0.008351916,0.001076601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01246321,"about_ca_system_score_gemma":0.03859768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001439182,"about_ca_topic_score_gemma":0.001820005,"domain_scores_codex":[0.08967642,0.8169882,0.05629118,0.00375465,0.03157216,0.001717349],"domain_scores_gemma":[0.08314075,0.8167006,0.03584313,0.02563556,0.03599839,0.002681611],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.006900907,0.001672131,0.02438294,0.05687477,0.008055001,0.0004911933,0.01383915,0.01649825,0.002025594,0.07251603,0.01105274,0.7856913],"study_design_scores_gemma":[0.009664965,0.01359107,0.03796385,0.1688174,0.01108739,0.0008874612,0.0134084,0.05756412,0.008895292,0.6094615,0.06715006,0.001508449],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07715164,0.04807249,0.6421268,0.08726498,0.002532266,0.1141509,0.001289104,0.0006705755,0.02674118],"genre_scores_gemma":[0.2077622,0.007661933,0.708634,0.00747366,0.000710876,0.06674959,0.0003708832,0.000146909,0.0004899955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.204093,"threshold_uncertainty_score":0.2516831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5476786752950077,"score_gpt":0.6262087510629254,"score_spread":0.0785300757679177,"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."}}