{"id":"W2107223447","doi":"10.1101/gr.904303","title":"Software for Automated Analysis of DNA Fingerprinting Gels","year":2003,"lang":"en","type":"article","venue":"Genome Research","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"National Human Genome Research Institute; BC Cancer Agency; National Institutes of Health; Michael Smith Health Research BC; Canada's Michael Smith Genome Sciences Centre","keywords":"Restriction fragment; Biology; Terminal restriction fragment length polymorphism; Fragment (logic); Restriction fragment length polymorphism; Restriction site; Genome; Restriction enzyme; Computational biology; Restriction digest; Restriction map; Software; Bacterial artificial chromosome; Genetics; Fingerprint (computing); DNA profiling; DNA; Computer science; Artificial intelligence; Polymerase chain reaction; Algorithm; Gene; Base sequence","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":[0.0009648001,0.00007385807,0.0001502175,0.0002103454,0.0001239304,0.00001086693,0.0002129265,0.0001387023,0.00003636001],"category_scores_gemma":[0.0004582875,0.00007231937,0.0001337367,0.0007459779,0.0001029284,8.859553e-7,0.00008916439,0.00007443384,0.000003114723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001257692,"about_ca_system_score_gemma":0.00008833288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001029264,"about_ca_topic_score_gemma":0.000009773465,"domain_scores_codex":[0.9989854,0.0001123135,0.0001823084,0.0003066713,0.000114301,0.0002990175],"domain_scores_gemma":[0.9990328,0.00004449941,0.00005055663,0.0004364885,0.0003830081,0.00005264975],"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":[0.000009967652,0.00004000827,0.001348248,0.00001726687,0.0002823259,3.205808e-7,0.00001342557,0.0001261659,0.9956707,0.001157842,0.0004170633,0.0009166826],"study_design_scores_gemma":[0.0002371727,0.0002595275,0.00740789,0.000005382235,0.0001175954,0.00000271418,0.00004886935,0.0006189123,0.8619676,0.0004465681,0.1286984,0.0001894445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8575503,0.0005921767,0.1395998,0.00007097637,0.00001205106,0.0005692687,0.00009414487,0.00006009838,0.00145121],"genre_scores_gemma":[0.9667808,0.00009135269,0.03209801,0.00003233882,0.00002120548,0.0002129664,0.0003206933,0.00001593415,0.0004267265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1337031,"threshold_uncertainty_score":0.2949098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04586154721941497,"score_gpt":0.3938830017010043,"score_spread":0.3480214544815893,"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."}}