{"id":"W4404356949","doi":"10.3389/fphot.2024.1502799","title":"Estimating retinal blood oxygenation from diffuse reflectance spectra of semi-infinite tissue using principal component analysis","year":2024,"lang":"en","type":"article","venue":"Frontiers in Photonics","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Héma-Québec; Université Laval","funders":"","keywords":"Principal component analysis; Reflectivity; Oxygenation; Diffuse reflection; Retinal; Diffuse reflectance infrared fourier transform; Component (thermodynamics); Biomedical engineering; Medicine; Chemistry; Materials science; Ophthalmology; Internal medicine; Optics; Artificial intelligence; Physics; Computer science; Biochemistry","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":[0.0002924663,0.0001798739,0.0005460394,0.0004856046,0.00003951824,0.00004602593,0.0001137307,0.0001099226,0.00003460628],"category_scores_gemma":[0.0001091289,0.0001752085,0.0001358147,0.001001287,0.00009782063,0.00008783522,0.00004046823,0.0004299492,0.000001293945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002651073,"about_ca_system_score_gemma":0.00009767182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001897286,"about_ca_topic_score_gemma":0.00001457042,"domain_scores_codex":[0.9984499,0.00004616651,0.0004913075,0.0004009839,0.0003386443,0.0002730483],"domain_scores_gemma":[0.9993493,0.00006205551,0.0001044699,0.0003389171,0.00006127422,0.00008401553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002997835,0.0008282856,0.06990601,0.0005771026,0.00180232,0.0005923585,0.002173769,0.00250997,0.9184218,0.0007780177,0.000441433,0.001669126],"study_design_scores_gemma":[0.0003971887,0.0001173977,0.00191676,0.0005017801,0.001233641,0.00001358473,0.00005235773,0.8293596,0.1648932,0.001174762,0.0001889279,0.0001507834],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7691354,0.001692272,0.2274185,0.0001173526,0.0003152274,0.0002141365,0.00002588571,0.0001600217,0.0009212878],"genre_scores_gemma":[0.5167057,0.00008633195,0.4830345,0.00002689744,0.00004122044,0.000005748622,0.00003880779,0.00001852655,0.00004231224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8268496,"threshold_uncertainty_score":0.7144796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482027982761091,"score_gpt":0.3198330265602304,"score_spread":0.3050127467326195,"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."}}