{"id":"W2313027821","doi":"10.1117/12.2212831","title":"Transcranial light-tissue interaction analysis","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","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":[],"consensus_categories":[],"category_scores_codex":[0.0004577854,0.0003032144,0.0006094289,0.0002327288,0.00006148648,0.00007336582,0.0004714568,0.0001980621,0.00005871888],"category_scores_gemma":[0.0006542479,0.0001977302,0.001027547,0.0005624067,0.000207149,0.000481014,0.00006727273,0.0002865767,0.00000336475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002131927,"about_ca_system_score_gemma":0.00003539968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001161765,"about_ca_topic_score_gemma":1.593746e-7,"domain_scores_codex":[0.9978284,1.252729e-8,0.0006925819,0.0004254044,0.0006661144,0.0003875338],"domain_scores_gemma":[0.997893,0.0001312209,0.0002610799,0.00007766984,0.00142694,0.0002101126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002448126,0.0001780856,0.001030215,0.0002114269,0.001242378,2.024086e-7,0.0001055634,0.000002316087,0.8237708,0.1698062,0.002614764,0.0007932998],"study_design_scores_gemma":[0.001590583,0.0008548053,0.001865755,0.0005267031,0.001723777,0.0000333905,0.0003816174,0.00382334,0.9774083,0.001181999,0.01026202,0.0003476958],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754144,0.00004983454,0.0006817107,0.01786893,0.0001638066,0.0004863332,0.00002895479,0.0001961174,0.00510991],"genre_scores_gemma":[0.8655249,0.0001450327,0.1326333,0.0002048365,0.0005287107,0.0001223341,0.000006755969,0.00006272077,0.0007713682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1686242,"threshold_uncertainty_score":0.8063205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996067092588811,"score_gpt":0.26992182351547,"score_spread":0.2599611525895819,"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."}}