{"id":"W4417116907","doi":"10.1016/j.ynirp.2025.100306","title":"Using, misusing, and improving online machine learning-based meta-analysis of neuroimaging published data: A perspective on NeuroQuery","year":2025,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Carleton University","keywords":"Perspective (graphical); Context (archaeology); Neuroimaging; Reliability (semiconductor); Interpretability; Scientific literature","routes":{"ca_aff":true,"ca_fund":true,"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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008792958,0.000447966,0.001265253,0.001410261,0.0004335541,0.0002482349,0.0003825012,0.00006442127,0.00005510417],"category_scores_gemma":[0.05010704,0.0004053937,0.0005500796,0.002575997,0.0003803429,0.0006720116,0.0008231887,0.0007271828,4.761901e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009442358,"about_ca_system_score_gemma":0.0002518998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001061818,"about_ca_topic_score_gemma":0.0001694859,"domain_scores_codex":[0.9949329,0.0006655768,0.0007963327,0.00247117,0.0007305614,0.0004034006],"domain_scores_gemma":[0.9921505,0.004688851,0.000867155,0.001847234,0.0003482885,0.00009797853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006371202,0.002907069,0.04069053,0.0004682937,0.02558947,0.008843053,0.000358154,0.1080162,0.8075445,0.001283845,0.002477645,0.001184205],"study_design_scores_gemma":[0.0009107881,0.0004466383,0.02732229,0.00002829918,0.09750699,0.0004029299,0.0001511432,0.831179,0.03592856,0.0004930492,0.004709071,0.0009212124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9483838,0.002452569,0.007742801,0.03032912,0.001769142,0.001760869,0.0007723205,0.0008508801,0.005938501],"genre_scores_gemma":[0.9924251,0.00001640704,0.0005156355,0.00647386,0.00003813579,0.00001101482,0.0000368944,0.00005001295,0.0004329331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7716159,"threshold_uncertainty_score":0.9998398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.155000680718986,"score_gpt":0.3676339897096371,"score_spread":0.2126333089906511,"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."}}