{"id":"W2886992206","doi":"10.1177/0300985818785705","title":"Observational Study Design in Veterinary Pathology, Part 1: Study Design","year":2018,"lang":"en","type":"article","venue":"Veterinary Pathology","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Observational study; Causality (physics); Selection (genetic algorithm); Medicine; Computer science; Pathology; Management science; Medical physics; Data science; Medical education; 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":[0.2994537,0.00131467,0.002086468,0.002373472,0.002208908,0.00291203,0.003026497,0.004277807,0.00651984],"category_scores_gemma":[0.3718453,0.001381043,0.001380071,0.003579998,0.005218281,0.002998641,0.002683159,0.003654846,0.001912111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003000699,"about_ca_system_score_gemma":0.007612603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009625147,"about_ca_topic_score_gemma":0.002226553,"domain_scores_codex":[0.6862416,0.2681074,0.02529723,0.004511822,0.01492511,0.0009168675],"domain_scores_gemma":[0.6110741,0.2975745,0.03282087,0.03336775,0.02251312,0.002649616],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003969663,0.001026449,0.06476593,0.03647676,0.0007833341,0.001055373,0.01567851,0.002325018,0.006132056,0.165174,0.1261497,0.5764633],"study_design_scores_gemma":[0.002909069,0.01131713,0.06270482,0.04549871,0.001326844,0.003323189,0.006073061,0.01019575,0.008199214,0.1819282,0.6660485,0.0004755308],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01683356,0.02832312,0.7270279,0.02876219,0.02257576,0.161804,0.001739306,0.0004813118,0.01245294],"genre_scores_gemma":[0.05513401,0.010959,0.5436361,0.01804849,0.008081223,0.3595482,0.0005880313,0.0002089405,0.00379594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7005463,"threshold_uncertainty_score":0.8638983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2746908880698031,"score_gpt":0.3861679257146809,"score_spread":0.1114770376448778,"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."}}