{"id":"W7091325820","doi":"10.5281/zenodo.17354102","title":"Neurobagel CLI: Command line tool for Neurobagel data parsing and annotation","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Parsing; Annotation; Python (programming language); Line (geometry); Simple (philosophy)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001935984,0.0001735009,0.0001434105,0.0001098115,0.0006691281,0.0002271976,0.0007273253,0.0001424501,0.0003102568],"category_scores_gemma":[0.0002299852,0.0001974135,0.00002998927,0.0001448018,0.0001057624,0.00001039342,0.001133633,0.0001631895,0.00004980549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001687201,"about_ca_system_score_gemma":0.000007619424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007380549,"about_ca_topic_score_gemma":0.000001295433,"domain_scores_codex":[0.9987887,0.00008497732,0.0001819144,0.0006212194,0.00008601897,0.0002371784],"domain_scores_gemma":[0.9988303,0.00001008028,0.0001313128,0.0008107371,0.0001612336,0.00005635697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004319938,0.00004946335,5.723401e-7,0.0001026783,0.00002962952,6.740437e-7,0.000009552808,0.000008244652,0.06473421,0.0007116702,0.8844192,0.0498909],"study_design_scores_gemma":[0.0003172375,0.0001947005,0.0000117174,0.0000426554,0.00002846227,0.00001492022,0.000008128111,0.0001988778,0.003436615,0.0001180925,0.9954491,0.0001795183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0007340856,0.001840982,0.8109546,0.001295559,0.0001472362,0.00309941,0.008486478,0.001063582,0.172378],"genre_scores_gemma":[0.01909076,0.01778319,0.0754158,0.003606824,0.002523003,0.000004295123,0.2936864,0.02205152,0.5658382],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7355388,"threshold_uncertainty_score":0.8050288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0300701179790695,"score_gpt":0.3245563063659982,"score_spread":0.2944861883869287,"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."}}