{"id":"W4393476886","doi":"10.5281/zenodo.5173100","title":"Breakpoints into the wild: an exploratory study","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Breakpoint; Biology; Genetics","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":[0.001315167,0.0009095437,0.0007622009,0.004166066,0.0009777052,0.001503179,0.00206388,0.001276219,0.02481223],"category_scores_gemma":[0.007910061,0.0003219487,0.0008561299,0.006077767,0.0005148015,0.001403969,0.001594314,0.001645302,0.02416987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008798518,"about_ca_system_score_gemma":0.001217545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01263264,"about_ca_topic_score_gemma":0.03680642,"domain_scores_codex":[0.9985947,0.0002148434,0.000175717,0.0003977307,0.0004560631,0.0001609262],"domain_scores_gemma":[0.9941167,0.002340136,0.0004317255,0.001587026,0.001191896,0.0003325346],"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":[0.0007109894,0.0002232679,0.01101221,0.001352858,0.00005683678,0.000464446,0.0004176307,0.001133153,0.001244733,0.003022969,0.953647,0.02671389],"study_design_scores_gemma":[0.0002881687,0.0001037359,0.02651616,0.0003830156,0.0000624225,0.0006477621,0.001278912,0.001732456,0.001963689,0.00350828,0.9634529,0.00006257329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00803105,0.0003168707,0.0009909389,0.0002031999,0.00007191848,0.00006818292,0.9857701,0.001276008,0.003271746],"genre_scores_gemma":[0.006980927,0.0001527611,0.003128963,0.00006480647,0.00001224186,0.0001651037,0.9872766,0.0002990774,0.001919401],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02481223,"threshold_uncertainty_score":0.08300513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05023936627456303,"score_gpt":0.3019637521397403,"score_spread":0.2517243858651773,"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."}}