{"id":"W4249559743","doi":"10.1002/9781119061199.ch15","title":"Computer imaging","year":2017,"lang":"en","type":"other","venue":"","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital","funders":"Division of Computer and Network Systems","keywords":"Thresholding; Computer science; Computer vision; Artificial intelligence; Cytogenetics; Photography; Karyotype; Resolution (logic); Image quality; Chromosome; Computer graphics (images); Image (mathematics); Pattern recognition (psychology); Biology; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001180784,0.0009532588,0.0008323581,0.002575145,0.000798601,0.002977791,0.001863654,0.001345727,0.1527449],"category_scores_gemma":[0.002603515,0.0005656026,0.0006833646,0.002169595,0.0005049066,0.002013047,0.001876557,0.00144138,0.08294208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008589169,"about_ca_system_score_gemma":0.000978425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001297107,"about_ca_topic_score_gemma":0.001869689,"domain_scores_codex":[0.9987765,0.0001262511,0.00007427664,0.0002754046,0.0006756261,0.00007191446],"domain_scores_gemma":[0.9988895,0.000269907,0.00004007022,0.000256218,0.0004938223,0.00005044553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001315933,0.00005076781,0.0004791169,0.0006103108,0.00003990443,0.000296573,0.0002755757,0.001895275,0.02696362,0.02787287,0.3140902,0.6272942],"study_design_scores_gemma":[0.00001958708,0.00003236704,0.0006171818,0.0001285873,0.00001619837,0.0008787236,0.00007590058,0.008041807,0.0139408,0.005466577,0.9707463,0.00003602955],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.003811275,0.005001339,0.5664812,0.001455028,0.001290368,0.0007426549,0.005528295,0.03720735,0.3784825],"genre_scores_gemma":[0.03608921,0.006946824,0.5090274,0.001954828,0.0004444701,0.001559193,0.01121433,0.006618018,0.4261457],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1527449,"threshold_uncertainty_score":0.5109825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005520367919791311,"score_gpt":0.2191403891284911,"score_spread":0.2136200212086998,"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."}}