{"id":"W2023855780","doi":"10.1002/hbm.20248","title":"Inference for magnitudes and delays of responses in the FIAC data using BRAINSTAT/FMRISTAT","year":2006,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Smoothing; Inference; Novelty; Magnitude (astronomy); Computer science; Voxel; Mathematics; Psychology; Artificial intelligence; Statistics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.009656928,0.001787902,0.001802885,0.002163118,0.0007088506,0.001690569,0.002657828,0.001126308,0.01882],"category_scores_gemma":[0.03524536,0.001583597,0.002854237,0.001564232,0.0008668202,0.001354106,0.001167105,0.002514073,0.003679668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007311089,"about_ca_system_score_gemma":0.002680784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01067839,"about_ca_topic_score_gemma":0.0121954,"domain_scores_codex":[0.9978054,0.0007802107,0.0001849423,0.0007244426,0.0003718219,0.0001330927],"domain_scores_gemma":[0.9892791,0.008185069,0.000572691,0.001156981,0.0006518452,0.0001543598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005530064,0.0007785041,0.03967945,0.002654797,0.005899108,0.001442045,0.00139437,0.2081985,0.1469992,0.03116193,0.06817617,0.4880858],"study_design_scores_gemma":[0.0005138444,0.0004472757,0.02474944,0.00005813627,0.0007786393,0.0005232003,0.00009546245,0.8667091,0.05564883,0.03664909,0.01356305,0.0002639405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02475664,0.00007017351,0.9455063,0.0001755735,0.00008189966,0.0003208483,0.005915427,0.02258673,0.0005863499],"genre_scores_gemma":[0.1297493,0.00009200371,0.8529053,0.0002094437,0.00005034401,0.001948183,0.005620986,0.007643319,0.001781077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01882,"threshold_uncertainty_score":0.06295913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.32076986253226,"score_gpt":0.4558225273935523,"score_spread":0.1350526648612923,"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."}}