{"id":"W1556921190","doi":"10.1109/pacrim.2003.1235956","title":"A pipeline structure for analysis of DNA microarrays","year":2004,"lang":"en","type":"article","venue":"","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Pipeline (software); Computer science; DNA microarray; Modular design; Noise (video); Image processing; Architecture; Image (mathematics); Artificial intelligence; Pattern recognition (psychology); Biology; Gene; Genetics; Programming language","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":[0.0005267898,0.000795476,0.0004378306,0.0006976756,0.000457168,0.0007663341,0.001238048,0.0006746305,0.008251485],"category_scores_gemma":[0.0007473917,0.0006146758,0.000645243,0.000853985,0.0004739643,0.001231276,0.0006086528,0.0009592524,0.003988999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000601397,"about_ca_system_score_gemma":0.0007394905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009630531,"about_ca_topic_score_gemma":0.001241509,"domain_scores_codex":[0.9995483,0.00005948072,0.00002700988,0.0001200475,0.0002020136,0.00004320581],"domain_scores_gemma":[0.9996636,0.00008226206,0.00002655175,0.00008861663,0.0001119719,0.00002688362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006233423,0.0001337497,0.0009610828,0.0007569367,0.00009719653,0.0003467972,0.0001783234,0.02012003,0.5686867,0.05305025,0.01483853,0.3402071],"study_design_scores_gemma":[0.000176585,0.001213698,0.002572291,0.00008706696,0.0001571366,0.001144342,0.00005621224,0.3843285,0.4035048,0.04835876,0.1582455,0.0001550833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00427185,0.000223549,0.9889172,0.0001051685,0.0000707099,0.0001104487,0.0002896953,0.004621975,0.001389425],"genre_scores_gemma":[0.04533602,0.0002770108,0.9487206,0.0001189387,0.00005579421,0.0002900464,0.001098883,0.0002117448,0.00389089],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008251485,"threshold_uncertainty_score":0.02760398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269084731617112,"score_gpt":0.2767763717581102,"score_spread":0.2640855244419391,"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."}}