{"id":"W6927633257","doi":"10.3389/fgene.2021.698595.s001","title":"Data_Sheet_1_Analysis of Sequence and Copy Number Variants in Canadian Patient Cohort With Familial Cancer Syndromes Using a Unique Next Generation Sequencing Based Approach.zip","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copy-number variation; Penetrance; Cancer; Genetic testing; DNA sequencing; Genetic predisposition; Sequence (biology); Mutation; Multiplex","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008752838,0.0006654962,0.0008015548,0.004544453,0.001495273,0.001154188,0.001484131,0.0007606054,0.2455008],"category_scores_gemma":[0.008019835,0.0004514548,0.0006773837,0.006235172,0.0003119644,0.0005424222,0.0006322333,0.0005241116,0.02295287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004674666,"about_ca_system_score_gemma":0.009323701,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.62388,"about_ca_topic_score_gemma":0.6926611,"domain_scores_codex":[0.9991792,0.00004372769,0.0001217153,0.0001607752,0.0003351968,0.0001594092],"domain_scores_gemma":[0.9929449,0.001503719,0.0007828497,0.0006042538,0.003400524,0.0007637595],"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":[0.0007425188,0.0001267396,0.0916831,0.00124363,0.0001047711,0.0005755991,0.0002197988,0.0005685688,0.001032978,0.0008771641,0.8609014,0.0419238],"study_design_scores_gemma":[0.0009965893,0.0002125122,0.4950629,0.001209606,0.000160356,0.001626653,0.0004550916,0.001373395,0.00151345,0.001229299,0.4960147,0.0001453363],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003091278,0.00006458638,0.0001891847,0.0002008376,0.00001821562,0.0002787934,0.9913533,0.0001802681,0.004623474],"genre_scores_gemma":[0.02883097,0.0004887979,0.00343274,0.0005976217,0.00006489727,0.001969841,0.9504222,0.0002029391,0.01399004],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.37612,"threshold_uncertainty_score":0.8212819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1380407710468151,"score_gpt":0.3209899469766053,"score_spread":0.1829491759297902,"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."}}