{"id":"W2166215223","doi":"10.1136/bjo.2008.141945","title":"Comparison between confocal scanning laser tomography, scanning laser polarimetry and optical coherence tomography on the ability to detect localised retinal nerve fibre layer defects in glaucoma patients","year":2008,"lang":"en","type":"article","venue":"British Journal of Ophthalmology","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital Maisonneuve-Rosemont; Dalhousie University","funders":"","keywords":"Optical coherence tomography; Scanning laser polarimetry; Medicine; Glaucoma; Retinal; Ophthalmology; Nerve fiber layer; Tomography; Confocal; Optic nerve; Optics; Radiology","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":[0.0007827154,0.0002857276,0.0008780163,0.0003964051,0.0002396141,0.00004920434,0.0002674608,0.000278628,0.000089181],"category_scores_gemma":[0.0006981689,0.0002439562,0.0002893819,0.000705684,0.0006302511,0.0001093449,0.0001103159,0.00121847,0.000005121022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006161336,"about_ca_system_score_gemma":0.0001136622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003518607,"about_ca_topic_score_gemma":0.00001129023,"domain_scores_codex":[0.9970742,0.00049369,0.0008859459,0.0003991254,0.0005593108,0.0005877629],"domain_scores_gemma":[0.9980348,0.000659289,0.0002928159,0.0002203112,0.0003363447,0.000456472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001100723,0.0003145171,0.9893276,0.00005903054,0.00007819841,0.006064058,0.0001611865,0.000008823777,0.0003714111,0.000004454643,0.0006234642,0.001886549],"study_design_scores_gemma":[0.002530119,0.003929788,0.9668004,0.0008240994,0.00009673458,0.02331803,0.0002465846,0.00001983432,0.00188327,0.00006863324,0.00004816472,0.0002343214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973483,0.0007375593,0.00004763245,0.0003975316,0.0001534623,0.0004915922,0.00002049147,0.00001368477,0.0007897392],"genre_scores_gemma":[0.9986961,0.00000906823,0.0008799704,0.0002481193,0.0001060543,0.000005924569,0.00001214419,0.00003004829,0.00001250887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02252716,"threshold_uncertainty_score":0.9948243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235881893601195,"score_gpt":0.28820694668964,"score_spread":0.2646187573295205,"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."}}