{"id":"W2799617104","doi":"","title":"Preliminary study of t0 , a sigma-lognormal parameter extracted from young children’s controlled scribbles","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Log-normal distribution; Sigma; Statistics; Six Sigma; Mathematics; Computer science; Physics; Engineering; Operations management","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":[0.0004427829,0.0003441758,0.0001930003,0.001515529,0.0001133344,0.0004581812,0.0002288636,0.0003127461,0.001679526],"category_scores_gemma":[0.004664625,0.000109471,0.0002088036,0.001272955,0.0002971358,0.000439467,0.0002759634,0.0003141186,0.0003943329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001429643,"about_ca_system_score_gemma":0.0002390533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002468888,"about_ca_topic_score_gemma":0.00223659,"domain_scores_codex":[0.9998148,0.00003812912,0.00001654671,0.00005461593,0.00004847313,0.00002737298],"domain_scores_gemma":[0.9978955,0.001333479,0.0002253771,0.0001733223,0.0002719033,0.0001003118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001238924,0.0001842129,0.2595977,0.0009334619,0.0001655632,0.002586759,0.005588985,0.03435352,0.29848,0.006395687,0.002026625,0.3884486],"study_design_scores_gemma":[0.0000214833,0.000413858,0.7873029,0.0001152233,0.00008191245,0.004113082,0.002165101,0.1479749,0.04637771,0.005686377,0.005652782,0.00009458784],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930294,0.0003113544,0.06502049,0.00004170343,0.00001268852,0.00003758447,0.001092153,0.0002966324,0.002893522],"genre_scores_gemma":[0.9885988,0.0001480703,0.01019598,0.000006569149,0.000005573304,0.00001740898,0.0005695376,0.00006764384,0.0003904204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002468888,"threshold_uncertainty_score":0.005618632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02538295001655205,"score_gpt":0.2581187690997886,"score_spread":0.2327358190832365,"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."}}