{"id":"W4391825703","doi":"10.15405/ejsbs.342","title":"Selecting Questionnaire Items for a specific Population Post COVID","year":2024,"lang":"en","type":"article","venue":"The European Journal of Social & Behavioural Sciences","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Relevance (law); Psychology; Charter; Selection (genetic algorithm); Population; Applied psychology; Medical education; Medicine; Computer science; Political science; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00746685,0.0004840368,0.0004171962,0.002436324,0.001279163,0.001146907,0.0006214239,0.0008863254,0.01233078],"category_scores_gemma":[0.01662182,0.0003222177,0.0005011279,0.001509876,0.000548086,0.001078309,0.001724615,0.0008867064,0.005445049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420033,"about_ca_system_score_gemma":0.002433408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002217563,"about_ca_topic_score_gemma":0.004720401,"domain_scores_codex":[0.9969044,0.001340844,0.0004031206,0.0002891278,0.0005539241,0.0005085266],"domain_scores_gemma":[0.9925658,0.002208105,0.0005300338,0.0004966587,0.003596607,0.000602687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007388382,0.001721059,0.3197369,0.002022547,0.00004647806,0.001663422,0.1549367,0.0006116932,0.03320985,0.004635843,0.04121664,0.4394601],"study_design_scores_gemma":[0.0001486501,0.003535819,0.5598564,0.001125088,0.00005550631,0.0009967273,0.1602148,0.002076681,0.008674173,0.002157049,0.2609703,0.0001887128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.917295,0.0002822626,0.02256044,0.001639761,0.0003206367,0.025453,0.003774208,0.000436474,0.02823825],"genre_scores_gemma":[0.7589484,0.001122699,0.1076593,0.001960448,0.0001665755,0.08843994,0.005639766,0.0002432436,0.03581973],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01233078,"threshold_uncertainty_score":0.04125053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05684517714150857,"score_gpt":0.3427204950614821,"score_spread":0.2858753179199736,"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."}}