{"id":"W4393495129","doi":"10.5281/zenodo.3234158","title":"Analysis of Huntingtin BioID Datasets 2019/04/09","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Huntingtin; Computational biology; Biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002611803,0.001129612,0.001046425,0.002995048,0.001309644,0.001785,0.00173275,0.001138964,0.04432651],"category_scores_gemma":[0.005458661,0.0003673631,0.001140692,0.003038123,0.0003214669,0.0008103062,0.002025265,0.001497152,0.03642301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465056,"about_ca_system_score_gemma":0.002854917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00838257,"about_ca_topic_score_gemma":0.01730917,"domain_scores_codex":[0.9983028,0.0001891932,0.0001589562,0.000470403,0.0006356182,0.0002429794],"domain_scores_gemma":[0.9964162,0.0004713047,0.0002618957,0.0008691538,0.001343751,0.0006375788],"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":[0.001031621,0.0002228763,0.009234328,0.001249521,0.0003869991,0.000261983,0.00008938808,0.0009108979,0.01369772,0.001634641,0.9539155,0.0173646],"study_design_scores_gemma":[0.001095473,0.0005658336,0.09767759,0.000412165,0.0002373539,0.0005170327,0.0003324661,0.008824551,0.03021998,0.003554795,0.8563946,0.0001681694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004775428,0.0001402628,0.0006632115,0.0002542107,0.0001514231,0.0001669274,0.9885821,0.002731952,0.002534353],"genre_scores_gemma":[0.002929354,0.00004223005,0.001737165,0.00007421712,0.00001322794,0.00015947,0.9938655,0.0001947524,0.0009839578],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04432651,"threshold_uncertainty_score":0.1482869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646170450132879,"score_gpt":0.2969019581369846,"score_spread":0.2804402536356558,"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."}}