{"id":"W3030872057","doi":"10.1002/jrsm.1425","title":"Development and validation of study filters for identifying controlled non‐randomized studies in <scp>PubMed</scp> and Ovid <scp>MEDLINE</scp>","year":2020,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Hamilton Health Sciences; Impact","funders":"","keywords":"MEDLINE; Computer science; Randomized controlled trial; Medical physics; Filter (signal processing); Medicine; Information retrieval; Surgery","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5389391,0.0003841484,0.008404632,0.00125852,0.0003317522,0.000681991,0.001056277,0.0001090006,0.00004030132],"category_scores_gemma":[0.7989889,0.0002027669,0.000853867,0.001946554,0.0004449857,0.000307722,0.0005542744,0.0002684673,0.0000194862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007053951,"about_ca_system_score_gemma":0.0001552208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000127266,"about_ca_topic_score_gemma":0.00001564054,"domain_scores_codex":[0.8593397,0.1159703,0.01324204,0.002293329,0.008078297,0.00107632],"domain_scores_gemma":[0.2317196,0.7564896,0.005084323,0.00219184,0.0037971,0.0007175697],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.004689531,0.001405383,0.03786042,0.007200648,0.01918405,0.00005999937,0.3362355,0.0003936166,0.01911665,0.0009659862,0.02440045,0.5484878],"study_design_scores_gemma":[0.1344396,0.0005317954,0.01764089,0.001073909,0.003519061,0.0000111841,0.6043398,0.08743389,0.1102046,0.01154381,0.02882134,0.0004401043],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8926789,0.005228675,0.09154469,0.0004364218,0.0001197295,0.009451983,0.000007972299,0.000007762125,0.000523937],"genre_scores_gemma":[0.6208643,0.0005905073,0.3713063,0.00005932773,0.00009190489,0.005633731,0.000002160767,0.00003329381,0.001418507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6405193,"threshold_uncertainty_score":0.8268593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8992365636946418,"score_gpt":0.6515213976464072,"score_spread":0.2477151660482346,"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."}}