{"id":"W2038970916","doi":"10.1364/boe.2.001268","title":"In vivo volumetric imaging of chicken retina with ultrahigh-resolution spectral domain optical coherence tomography","year":2011,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Retina; Optical coherence tomography; Retinal; Preclinical imaging; Image resolution; Ganglion cell layer; Tomography; Optics; Materials science; Biomedical engineering; In vivo; Ophthalmology; Medicine; Biology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0002681384,0.0002726113,0.0003582207,0.0006432564,0.00004326177,0.00002491227,0.0005002444,0.0001740026,0.000262292],"category_scores_gemma":[0.00004793083,0.0002466974,0.0001013098,0.002296214,0.0008825944,0.0002129949,0.00005710785,0.0004129809,0.00001302773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004973938,"about_ca_system_score_gemma":0.00003510844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006468346,"about_ca_topic_score_gemma":0.00001254804,"domain_scores_codex":[0.9978903,0.00003777885,0.0005560736,0.0003728236,0.0005430582,0.000599969],"domain_scores_gemma":[0.9989014,0.0001402876,0.00007375709,0.0004688784,0.00008316917,0.0003325306],"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":[0.0009346098,0.006211988,0.120318,0.001618256,0.0007023254,0.000664739,0.006419867,0.0013763,0.6495605,0.1982104,0.007067135,0.006915857],"study_design_scores_gemma":[0.01243575,0.003692735,0.3683459,0.002249629,0.0006670026,0.0003703922,0.00283363,0.1309391,0.4251073,0.03836153,0.008437971,0.006559047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8376513,0.0003834867,0.1313556,0.0001266922,0.0002678951,0.000770533,0.00008548256,0.0003952732,0.02896374],"genre_scores_gemma":[0.8784031,0.00003205817,0.1213306,0.00001408778,0.0000664591,0.00009703487,0.00000869845,0.00003633416,0.00001171244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.248028,"threshold_uncertainty_score":0.9999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00944944874251635,"score_gpt":0.20948133930175,"score_spread":0.2000318905592337,"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."}}