{"id":"W2971988795","doi":"10.1017/cjn.2019.265","title":"Image Analysis in Neuropathology: Hue-Saturation-Intensity vs. Colour Deconvolution","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Artificial intelligence; RGB color model; Computer vision; Computer science; Digital image; Image processing; Pattern recognition (psychology); Pixel; Image quality; Hue; Color space; Mathematics; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006798028,0.0008898896,0.0005247951,0.001914455,0.0004526111,0.003333765,0.001785323,0.001915574,0.02072439],"category_scores_gemma":[0.01711689,0.0005481288,0.0008371043,0.0012597,0.001370026,0.002824887,0.002885296,0.003063657,0.008015163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084745,"about_ca_system_score_gemma":0.001029645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008722948,"about_ca_topic_score_gemma":0.001196948,"domain_scores_codex":[0.9981751,0.0007785163,0.0001244188,0.0002397632,0.0005748188,0.0001072228],"domain_scores_gemma":[0.9940054,0.003943409,0.0002507341,0.000335735,0.001098473,0.0003662781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006281572,0.0001806927,0.001932987,0.001976804,0.00007103729,0.0003497152,0.001110566,0.003870839,0.01725302,0.03796242,0.08514491,0.8495188],"study_design_scores_gemma":[0.0002453892,0.001200415,0.01273834,0.005377532,0.000178596,0.009651166,0.001991707,0.0801619,0.06723116,0.2071261,0.6135615,0.0005361311],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01334445,0.01633567,0.9096643,0.009818916,0.002572905,0.0005844634,0.0005465022,0.009452991,0.03767972],"genre_scores_gemma":[0.06970675,0.02211973,0.8805791,0.00333069,0.001082127,0.0007969789,0.0004257401,0.003169111,0.01878967],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02072439,"threshold_uncertainty_score":0.06932998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070000466039491,"score_gpt":0.2531198109133988,"score_spread":0.2424198062530039,"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."}}