{"id":"W2598530016","doi":"","title":"So many databases, such little clarity","year":2008,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Diverse academic research themes","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"PsycINFO; MEDLINE; Information retrieval; Computer science; Bibliographic database; CLARITY; Medicine; Database; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04978387,0.001537285,0.00370884,0.01568655,0.003465287,0.01786234,0.004350723,0.006653345,0.02904854],"category_scores_gemma":[0.2318173,0.001537937,0.00292392,0.02401838,0.004842024,0.02213061,0.007036253,0.006161717,0.01905314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00510855,"about_ca_system_score_gemma":0.01713995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003414458,"about_ca_topic_score_gemma":0.00550866,"domain_scores_codex":[0.9037149,0.05014227,0.02320723,0.004871527,0.01684331,0.001220674],"domain_scores_gemma":[0.7581731,0.1435728,0.02164442,0.0217388,0.05195152,0.002919312],"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":[0.0004115682,0.0001164813,0.002267126,0.06598393,0.001189527,0.0006708965,0.004281812,0.0003218487,0.001663893,0.09209689,0.3645939,0.4664021],"study_design_scores_gemma":[0.00009892199,0.00004573162,0.0009823786,0.04170714,0.0005129997,0.0008441549,0.002051777,0.0001729423,0.0004518726,0.03788367,0.9151723,0.00007610131],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004193068,0.3652109,0.07861566,0.4160142,0.02449217,0.001975911,0.01573361,0.002044525,0.09171996],"genre_scores_gemma":[0.06378084,0.374394,0.2051514,0.2931107,0.02176591,0.003654375,0.01439499,0.001601982,0.02214575],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9502161,"threshold_uncertainty_score":0.2632854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.214839889274884,"score_gpt":0.3758676353242985,"score_spread":0.1610277460494145,"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."}}