{"id":"W4221118345","doi":"10.1002/jrsm.1557","title":"Graphical Representation of Overlap for <scp>OVErviews</scp>: <scp>GROOVE</scp> tool","year":2022,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":257,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Universitat Autònoma de Barcelona; Instituto de Salud Carlos III; Fondo Nacional de Desarrollo Científico y Tecnológico; Agencia Nacional de Investigación y Desarrollo; Ministerio de Economía y Competitividad","keywords":"Computer science; Representation (politics); Matrix (chemical analysis); Data mining; Groove (engineering); Information retrieval; Matrix representation","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02745305,0.004495419,0.004384951,0.02552242,0.001549528,0.00745519,0.003275149,0.00340572,0.3926674],"category_scores_gemma":[0.2291997,0.002241502,0.006214094,0.02263466,0.001228643,0.007249856,0.008896836,0.003485478,0.04582697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004279048,"about_ca_system_score_gemma":0.0116785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005488462,"about_ca_topic_score_gemma":0.0076834,"domain_scores_codex":[0.9766036,0.01047001,0.006232019,0.001807258,0.004099635,0.000787535],"domain_scores_gemma":[0.7207233,0.2224521,0.01602809,0.007496173,0.03119052,0.002109875],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007098656,0.00007606467,0.001435358,0.07182443,0.0007438016,0.0003369006,0.001833122,0.001317281,0.001273066,0.01087078,0.8235494,0.08602998],"study_design_scores_gemma":[0.00206093,0.0001907793,0.004968543,0.02907642,0.0009702728,0.000547984,0.001170926,0.004962831,0.002174841,0.04883903,0.9045478,0.0004896424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.004021927,0.005863055,0.08508851,0.01303322,0.003136895,0.01812337,0.7080432,0.1179707,0.04471911],"genre_scores_gemma":[0.03595814,0.005413187,0.5960461,0.008694414,0.001441426,0.1039783,0.1881986,0.03092808,0.02934162],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9725469,"threshold_uncertainty_score":0.8662863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8564511360551862,"score_gpt":0.6584873612399715,"score_spread":0.1979637748152147,"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."}}