{"id":"W2103365019","doi":"10.1093/bioinformatics/btq271","title":"SLIMS—a user-friendly sample operations and inventory management system for genotyping labs","year":2010,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Computer science; User Friendly; Database; Java; Personalization; Interface (matter); Sample (material); Documentation; Source code; World Wide Web; User interface; Operating system","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":[0.0001915938,0.00009721658,0.00009525115,0.00003645461,0.0001539311,0.00004769769,0.0001276993,0.0001353784,0.000003297142],"category_scores_gemma":[0.00009913232,0.00008296433,0.00003672489,0.00003939999,0.0000842195,0.000005413552,0.0001115103,0.00006234247,0.000005774771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007247511,"about_ca_system_score_gemma":0.00002560268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007435999,"about_ca_topic_score_gemma":0.00005586723,"domain_scores_codex":[0.9994181,0.000007582313,0.0002118489,0.0001124284,0.00007274932,0.0001772814],"domain_scores_gemma":[0.9995982,0.00001681138,0.00004242741,0.0002231747,0.0000445695,0.00007479484],"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":[0.0003343732,0.0003440556,0.00840813,0.007809926,0.001142004,0.000009159414,0.003673145,0.0001963803,0.1446262,0.09665368,0.1077059,0.6290971],"study_design_scores_gemma":[0.0009997841,0.0002922222,0.0007718655,0.00004876973,0.00005504663,0.00002326732,0.002854323,0.01271047,0.01029127,0.00004670446,0.9715893,0.0003170208],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.541639,0.0004456853,0.4522115,0.0003262849,0.001222031,0.0009045449,0.0002084641,0.0001356125,0.002906969],"genre_scores_gemma":[0.3466998,0.0000920573,0.6516163,0.0003245899,0.0002540431,0.0001113562,0.0002942488,0.00001947661,0.0005880637],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8638834,"threshold_uncertainty_score":0.3383187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01331988542185686,"score_gpt":0.2546115274215406,"score_spread":0.2412916419996837,"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."}}