{"id":"W755151884","doi":"10.1007/978-3-319-02054-9_44","title":"Generating Master Assembly Sequence Using Consensus Trees","year":2013,"lang":"en","type":"book-chapter","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Sequence (biology); Consensus sequence; Computer science; Biology; Genetics; Base sequence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003763011,0.0003011184,0.0002382005,0.00008944508,0.00005698367,0.0001199466,0.00009366773,0.0002532956,0.001930721],"category_scores_gemma":[0.000003967406,0.0002808359,0.00005645234,0.00001056785,0.00002187798,0.0000712352,0.00002955812,0.0001964278,0.00014503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006631248,"about_ca_system_score_gemma":0.00002011631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002548637,"about_ca_topic_score_gemma":0.00001973843,"domain_scores_codex":[0.9991807,0.000003150548,0.000271915,0.000214219,0.000139025,0.0001909909],"domain_scores_gemma":[0.9996023,0.00002214431,0.00006515862,0.0001935156,0.00005779889,0.0000590905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.761603e-7,0.000001125019,0.000001800359,0.0001754624,0.00005288037,0.00001112822,0.00003591687,0.9856215,0.001642419,0.003842409,0.001262746,0.007351858],"study_design_scores_gemma":[0.00008549071,0.000008213873,0.000001725913,0.0001642123,0.00003548098,0.00001974397,0.000004596858,0.9821383,0.002166672,0.0004033244,0.01448763,0.0004845489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00234083,0.0004596221,0.04525406,0.0000200194,0.0004341727,0.0002354124,0.00001403768,0.0005372592,0.9507046],"genre_scores_gemma":[0.03965197,0.0001775717,0.1023185,0.0001504214,0.0005400953,0.00001056762,0.00006006007,0.0002585918,0.8568322],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09387238,"threshold_uncertainty_score":0.9999644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05219539175202875,"score_gpt":0.2296589001259481,"score_spread":0.1774635083739194,"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."}}