{"id":"W6958547288","doi":"10.6084/m9.figshare.15087452.v1","title":"Additional file 7 of InvertypeR: Bayesian inversion genotyping with Strand-seq data","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Bayesian probability; Inversion (geology); Pattern recognition (psychology); Bayes estimator; Bayes' theorem","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002301086,0.002183772,0.001894208,0.003167963,0.00149837,0.002417699,0.003209296,0.002004183,0.7677999],"category_scores_gemma":[0.01510067,0.001476875,0.001650607,0.003424915,0.0005280154,0.001693428,0.001711224,0.001984271,0.2614234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134614,"about_ca_system_score_gemma":0.002167968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008245327,"about_ca_topic_score_gemma":0.01779685,"domain_scores_codex":[0.9988422,0.0001776956,0.0001097066,0.00039541,0.0002963173,0.0001787662],"domain_scores_gemma":[0.9876719,0.008959963,0.0004892708,0.001244821,0.001123393,0.0005107368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002275187,0.00007836125,0.002554842,0.001399275,0.00008882585,0.0001159203,0.00009092197,0.0009120897,0.001108866,0.00086865,0.9859367,0.006617948],"study_design_scores_gemma":[0.003165861,0.0002031569,0.02356075,0.001371036,0.0003339534,0.0006583502,0.0004020016,0.005176775,0.007049417,0.01602121,0.9417254,0.0003321619],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001927015,0.00001747116,0.00131416,0.00005665959,0.00004244041,0.00004606625,0.9944469,0.002751446,0.001132013],"genre_scores_gemma":[0.004861233,0.0000732372,0.007572464,0.000474843,0.00006657463,0.0007276983,0.9742632,0.006669442,0.005291326],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7677999,"threshold_uncertainty_score":0.3312052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02269112861115326,"score_gpt":0.2094813891207722,"score_spread":0.1867902605096189,"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."}}