{"id":"W1983676139","doi":"10.1034/j.1399-0004.2001.600102.1.x","title":"A super sensor for DNA integrity: bigger is better","year":2001,"lang":"en","type":"article","venue":"Clinical Genetics","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Citation; Library science; Medical genetics; Medicine; Gerontology; Computer science; Genetics; Biology","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":[0.00477439,0.001538021,0.002600641,0.002259955,0.001717699,0.005865389,0.002464186,0.007353762,0.01859139],"category_scores_gemma":[0.01356056,0.001391765,0.001217696,0.001172925,0.004744889,0.01560395,0.003894306,0.009908088,0.005659884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001836505,"about_ca_system_score_gemma":0.001316938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008053769,"about_ca_topic_score_gemma":0.0007779336,"domain_scores_codex":[0.9945674,0.00114429,0.0002683823,0.001013135,0.002522779,0.0004840384],"domain_scores_gemma":[0.988435,0.003885012,0.001211985,0.00184857,0.003299864,0.001319556],"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":[0.001239462,0.0003569505,0.008986121,0.002081764,0.0003494005,0.0005704028,0.001200036,0.001010007,0.6875017,0.0516719,0.04143657,0.2035958],"study_design_scores_gemma":[0.0001899677,0.002612902,0.01430504,0.001140635,0.0006819569,0.01046291,0.00332163,0.01036757,0.5358284,0.1407465,0.2795097,0.0008327228],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1849263,0.1596175,0.2974036,0.2342879,0.02497709,0.0003387647,0.002566522,0.009987483,0.08589492],"genre_scores_gemma":[0.6294845,0.03295943,0.2016072,0.08202591,0.006473451,0.000438598,0.001431859,0.001743279,0.04383568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01859139,"threshold_uncertainty_score":0.06219435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139059923118061,"score_gpt":0.4134209934022182,"score_spread":0.2743610702841572,"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."}}