{"id":"W4393755888","doi":"10.5281/zenodo.846319","title":"Ros-Specific Huntingtin Interactions: Ip Optimization In Patient-Derived Cells","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Huntingtin; Chemistry; Cell biology; Biology; Biochemistry; Gene","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":[0.001507163,0.002093182,0.001718809,0.001721318,0.0005100734,0.001773056,0.001838612,0.002130022,0.01041419],"category_scores_gemma":[0.003720358,0.0004793046,0.001917398,0.001856653,0.0003575168,0.0006099871,0.00129153,0.001328979,0.01149649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001025801,"about_ca_system_score_gemma":0.001601581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004566604,"about_ca_topic_score_gemma":0.01197728,"domain_scores_codex":[0.9991933,0.0001250313,0.00008949322,0.0003519424,0.0001402865,0.00009998432],"domain_scores_gemma":[0.9990865,0.0004056744,0.00008127295,0.0002558056,0.0001164198,0.00005444463],"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":[0.001755105,0.0002958589,0.01563976,0.004758788,0.001039606,0.0005622412,0.0001177382,0.006984304,0.008926434,0.001593006,0.9198977,0.03842938],"study_design_scores_gemma":[0.002369894,0.0003290738,0.03745021,0.0008922337,0.001265204,0.001861549,0.0002065926,0.01799421,0.02171349,0.006945579,0.9088252,0.0001467146],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.009566745,0.001435938,0.002405259,0.0002771283,0.00008536513,0.00007676377,0.9801772,0.004440501,0.001535113],"genre_scores_gemma":[0.007235704,0.0003124277,0.003939621,0.0001594308,0.00001207449,0.0002252752,0.9871439,0.0002268529,0.0007446806],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01041419,"threshold_uncertainty_score":0.03483891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958457931297899,"score_gpt":0.2679908579158451,"score_spread":0.2484062786028661,"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."}}