{"id":"W7105922523","doi":"10.5281/zenodo.17630622","title":"Reseau de neurones Zoran🦋","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cognitive Science and Education Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic shortage; Python (programming language); Sigma","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001568673,0.0007236462,0.0004782008,0.0005539968,0.0006602093,0.001302676,0.00176751,0.0009185799,0.05595682],"category_scores_gemma":[0.0006536483,0.0002904869,0.0009945262,0.0004245981,0.0003573106,0.001662113,0.001092717,0.0009031838,0.01850258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001105662,"about_ca_system_score_gemma":0.0008433327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01186669,"about_ca_topic_score_gemma":0.0147032,"domain_scores_codex":[0.999826,0.000009458629,0.000009786494,0.00004628819,0.00006708405,0.00004139365],"domain_scores_gemma":[0.9998617,0.00001579383,0.000007143109,0.00002867182,0.00007175023,0.00001488766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007177614,0.00008239002,0.002168549,0.001315261,0.000210412,0.001254728,0.0004810603,0.07205296,0.09046284,0.1721061,0.1704484,0.4886996],"study_design_scores_gemma":[0.000139373,0.0002300305,0.00397669,0.0003331311,0.0001600403,0.001247243,0.0002466703,0.2449799,0.1245274,0.07114559,0.5528607,0.0001530868],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.09611119,0.005372252,0.560407,0.002284043,0.002646316,0.0003360842,0.01526874,0.0464543,0.2711201],"genre_scores_gemma":[0.4374847,0.00264384,0.2283954,0.0009081713,0.0002102223,0.0006271508,0.01511735,0.00462337,0.3099899],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9440432,"threshold_uncertainty_score":0.1871942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07149091412182365,"score_gpt":0.3327830998335,"score_spread":0.2612921857116763,"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."}}