{"id":"W3169915419","doi":"10.1017/9781108635462.006","title":"Research Consortia and Large-Scale Data Repositories for Studying Intelligence","year":2021,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Neuroimaging; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology","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":["metaresearch"],"category_scores_codex":[0.430364,0.002723651,0.007312259,0.06961545,0.004988135,0.01990451,0.0124354,0.008794961,0.06303545],"category_scores_gemma":[0.6756601,0.00337315,0.005085055,0.08779915,0.004863137,0.02469491,0.02348008,0.007906903,0.02768137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006446948,"about_ca_system_score_gemma":0.06551541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002981631,"about_ca_topic_score_gemma":0.003120863,"domain_scores_codex":[0.5757096,0.1932805,0.1372748,0.0287482,0.05935964,0.005627179],"domain_scores_gemma":[0.1623363,0.4131431,0.07653656,0.1960171,0.1333005,0.01866639],"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":[0.001600183,0.0003491559,0.01063769,0.03259754,0.002379733,0.0004850184,0.003801886,0.001051426,0.001086088,0.08498853,0.4747543,0.3862685],"study_design_scores_gemma":[0.001280412,0.0002513268,0.009612586,0.02595383,0.001217299,0.0003257084,0.001671799,0.001057294,0.001149003,0.05352266,0.9036522,0.000305895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.008742091,0.05369383,0.2301922,0.09723686,0.0364678,0.07028516,0.3716105,0.02260753,0.109164],"genre_scores_gemma":[0.04709822,0.02981475,0.3928301,0.01576123,0.009564898,0.2011881,0.2780182,0.00636378,0.01936073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.569636,"threshold_uncertainty_score":0.7024627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2008181586744021,"score_gpt":0.3207826808336363,"score_spread":0.1199645221592342,"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."}}