{"id":"W2156926979","doi":"10.1177/0163278706293400","title":"Developing Optimal Search Strategies for Retrieving Qualitative Studies in PsycINFO","year":2006,"lang":"en","type":"article","venue":"Evaluation & the Health Professions","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"PsycINFO; Qualitative research; Search engine indexing; Computer science; MEDLINE; Information retrieval; Qualitative property; Psychology; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.181933,0.003043033,0.006628532,0.05726057,0.002332201,0.007711102,0.004896262,0.003759201,0.04131854],"category_scores_gemma":[0.5119656,0.003703824,0.004777872,0.05075593,0.002148233,0.01270182,0.006892852,0.002699002,0.009696496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006469037,"about_ca_system_score_gemma":0.02067639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004966848,"about_ca_topic_score_gemma":0.01050706,"domain_scores_codex":[0.787705,0.1355262,0.06538658,0.002653799,0.007524932,0.001203384],"domain_scores_gemma":[0.4533477,0.4882955,0.01995919,0.01290169,0.02400179,0.001494039],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002232711,0.0003317371,0.002489704,0.2273656,0.001373743,0.001008936,0.014058,0.002220239,0.002834578,0.01382294,0.03225942,0.7000023],"study_design_scores_gemma":[0.01420475,0.003437061,0.01561246,0.3916049,0.01544358,0.002587032,0.04928174,0.02147097,0.01593485,0.1188873,0.3497227,0.001812616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0307831,0.05035282,0.4801766,0.01517648,0.001503594,0.3583389,0.03123265,0.006442388,0.0259935],"genre_scores_gemma":[0.02592879,0.01617332,0.7432199,0.000792691,0.0001273634,0.2088108,0.003268912,0.000346913,0.001331403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.818067,"threshold_uncertainty_score":0.9621654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8112156344634597,"score_gpt":0.7367197101535863,"score_spread":0.0744959243098734,"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."}}