{"id":"W4319596496","doi":"10.1063/5.0132123.1","title":"10.1063/5.0132123.1","year":2023,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008965422,0.00061407,0.0005215653,0.0004173719,0.00008635355,0.0005248463,0.0008583375,0.0005272189,0.0007961036],"category_scores_gemma":[0.0001332993,0.0006459296,0.0003465884,0.001286959,0.0001325477,0.0003879298,0.000188598,0.000719915,0.1207458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001105839,"about_ca_system_score_gemma":0.0000289744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000615442,"about_ca_topic_score_gemma":0.0001063292,"domain_scores_codex":[0.9976895,0.00001306214,0.0005213959,0.0005738211,0.0004980788,0.0007041337],"domain_scores_gemma":[0.9981311,0.0002883286,0.00007137255,0.001172022,0.00006468151,0.0002724837],"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":[0.000004977231,0.00005388613,0.000001512987,0.0001739833,0.000122358,0.00003477569,0.000003551039,0.0001099117,0.000005215258,0.00003515817,0.9962428,0.003211837],"study_design_scores_gemma":[0.0001564604,0.00008397327,0.00008790829,0.0000719562,0.00006603989,0.00001108068,0.00001204634,0.0002716982,0.000006927551,0.000421902,0.9980942,0.0007157815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004923169,0.0001708103,0.00009708539,0.00001584475,0.0004061307,0.0004911419,0.9797569,0.001900259,0.01711262],"genre_scores_gemma":[0.0005550435,0.00008768547,0.00005735981,0.00002597973,0.0003388108,0.0004562539,0.9961454,0.0001586383,0.002174811],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1199497,"threshold_uncertainty_score":0.9995992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996180619286251,"score_gpt":0.2263696071014733,"score_spread":0.2164078009086108,"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."}}