{"id":"W4281695863","doi":"10.5281/zenodo.6624790","title":"NiMARE: Neuroimaging Meta-Analysis Research Environment","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Neuroimaging; Meta-analysis; Psychology; Computer science; Data science; Neuroscience; Medicine; Internal medicine","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":[0.01612431,0.002697056,0.003646449,0.006027169,0.0007964799,0.006018159,0.005460544,0.002068197,0.4096482],"category_scores_gemma":[0.09250949,0.003064422,0.005505138,0.006827287,0.0006988338,0.003642448,0.006650374,0.003021044,0.2118838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001356596,"about_ca_system_score_gemma":0.005746954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003650171,"about_ca_topic_score_gemma":0.008802056,"domain_scores_codex":[0.9921251,0.003444719,0.001156004,0.001506412,0.001480521,0.0002872687],"domain_scores_gemma":[0.9594952,0.02583207,0.002601461,0.007680207,0.003356354,0.001034582],"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":[0.0005801216,0.00001933796,0.0006019722,0.007652295,0.001532637,0.0001121287,0.0001630086,0.0008122774,0.0005247479,0.005255983,0.9556316,0.02711395],"study_design_scores_gemma":[0.002594707,0.0001176739,0.002704798,0.002885808,0.001733056,0.0003890147,0.00005004543,0.003205623,0.002097517,0.03551084,0.9484085,0.0003023853],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0008828476,0.00277765,0.08000335,0.002394666,0.001335528,0.0009886331,0.6886598,0.2045799,0.01837758],"genre_scores_gemma":[0.01789872,0.003538593,0.2893484,0.004243476,0.001184,0.0154592,0.3321471,0.2956099,0.04057056],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9838757,"threshold_uncertainty_score":0.8420652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227985074848674,"score_gpt":0.2967167051487238,"score_spread":0.1739181976638564,"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."}}