{"id":"W4391023318","doi":"10.1007/s10439-023-03437-1","title":"Functional Assessment of Human Articular Cartilage Using Second Harmonic Generation (SHG) Imaging: A Feasibility Study","year":2024,"lang":"en","type":"article","venue":"Annals of Biomedical Engineering","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; Alberta Bone and Joint Health Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Cartilage; Biomedical engineering; Articular cartilage; Materials science; Indentation; Osteoarthritis; Image quality; Second-harmonic generation; Anatomy; Medicine; Optics; Pathology; Laser; Composite material; Image (mathematics); Artificial intelligence; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0004188664,0.0001302,0.0002843196,0.0002009118,0.00002971254,0.00001546446,0.00003432375,0.00004928598,0.0002607289],"category_scores_gemma":[0.00003198835,0.0001156382,0.0001341572,0.0002253967,0.00004397033,0.0000941426,0.00003054228,0.0001217503,0.000001792229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004641108,"about_ca_system_score_gemma":0.0001039136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007763601,"about_ca_topic_score_gemma":0.000002352719,"domain_scores_codex":[0.9987595,0.00002314934,0.0003884068,0.0002378674,0.0004064269,0.0001846678],"domain_scores_gemma":[0.9995251,0.00002557346,0.00004179582,0.0001804669,0.00008957201,0.0001375336],"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":[0.000009544417,0.0005208035,0.0009458823,0.0002344564,0.0000900287,0.0001071971,0.0001190808,0.00003874709,0.9964231,0.0001943427,0.0001172232,0.001199652],"study_design_scores_gemma":[0.002360078,0.002519299,0.01279956,0.0005255836,0.000340065,0.00007000969,0.0002042458,0.1032696,0.8772881,0.00006664592,0.0003277196,0.0002290799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909849,0.0008465622,0.007209968,0.0001614774,0.0003192676,0.000370634,0.00001680495,0.00006019692,0.00003014957],"genre_scores_gemma":[0.9988276,0.000003801911,0.0008210851,0.00002355471,0.0001849764,0.00001497904,0.00006375583,0.0000188798,0.00004132497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.119135,"threshold_uncertainty_score":0.4715589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09204887177402447,"score_gpt":0.3657182072996856,"score_spread":0.2736693355256611,"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."}}