{"id":"W6968551952","doi":"10.5281/zenodo.3490378","title":"MiRoR-P1-A scoping review describes methods used to identify, prioritize and display gaps in health research","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital","funders":"European Commission","keywords":"Health data; Health care; Data collection; MEDLINE; Context (archaeology)","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":[0.1276393,0.003163361,0.006632169,0.04819056,0.004118876,0.009801085,0.004863693,0.00685356,0.04939774],"category_scores_gemma":[0.2519754,0.003145534,0.01172555,0.04530584,0.002652307,0.007797067,0.009373656,0.003953054,0.01742717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008615903,"about_ca_system_score_gemma":0.0573316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006516567,"about_ca_topic_score_gemma":0.01920561,"domain_scores_codex":[0.8792616,0.04899933,0.04923349,0.003118127,0.01716538,0.002221991],"domain_scores_gemma":[0.7483935,0.1427928,0.02505635,0.01446443,0.06740487,0.001887934],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000713073,0.0001343675,0.00136032,0.6190512,0.001390546,0.0003292493,0.00307102,0.0007502396,0.001682576,0.01777092,0.1191989,0.2345476],"study_design_scores_gemma":[0.0003194571,0.0002572279,0.002573733,0.4493864,0.002845302,0.0003266197,0.001179829,0.00032066,0.001555822,0.007592995,0.5335209,0.0001209694],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"protocol","genre_gemma":"review","genre_scores_codex":[0.005919701,0.2672799,0.1191222,0.03478201,0.008844466,0.2907001,0.1447051,0.004262937,0.1243836],"genre_scores_gemma":[0.01910507,0.2153154,0.2887172,0.006795479,0.001701306,0.3882571,0.05484582,0.001407906,0.0238546],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8723606,"threshold_uncertainty_score":0.6750294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6687944842754141,"score_gpt":0.6776755385549141,"score_spread":0.008881054279500034,"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."}}