{"id":"W1505843021","doi":"10.1186/1471-2105-16-s5-s7","title":"Isomorphism and similarity for 2-generation pedigrees","year":2015,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Pedigree chart; Isomorphism (crystallography); Combinatorics; Partition (number theory); Integer (computer science); Mathematics; Computer science; Property (philosophy); Time complexity; Theoretical computer science; Biology; Genetics","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":[0.000374809,0.00007558315,0.0000852356,0.00004127451,0.00009372519,0.0001747255,0.0001887174,0.00004385423,0.000001033642],"category_scores_gemma":[0.0001515193,0.00006311868,0.00002260955,0.00006876361,0.00002123316,0.0003422939,0.00009257052,0.0000607894,0.00001173332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001125709,"about_ca_system_score_gemma":0.00006237863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009467873,"about_ca_topic_score_gemma":0.00001072862,"domain_scores_codex":[0.9994648,0.00001510088,0.0001670767,0.00008482678,0.0001390948,0.0001290837],"domain_scores_gemma":[0.9995103,0.0000473431,0.00007249122,0.0001910007,0.00007968961,0.00009918355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002955267,0.0001984715,0.01367904,0.0007112063,0.00004924883,0.000003337463,0.02476233,0.01444331,0.00006378852,0.2174651,0.2322019,0.4963926],"study_design_scores_gemma":[0.0003545017,0.00008695609,0.0002370804,0.000003800847,0.000003218144,0.0000107523,0.00007011275,0.9846244,0.00004375113,0.00121928,0.01325364,0.00009247247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002348841,0.00005926719,0.9953997,0.0004964101,0.0003047906,0.0001292563,0.000004813697,0.0001007253,0.001156174],"genre_scores_gemma":[0.01216471,0.000005239355,0.9869196,0.0003607115,0.0001935291,0.000009225887,0.00001655807,0.000003881217,0.0003265387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9701811,"threshold_uncertainty_score":0.2573905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09091666958478403,"score_gpt":0.2843398320754851,"score_spread":0.193423162490701,"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."}}