{"id":"W6930211326","doi":"10.5281/zenodo.12557897","title":"Pyenson, Huisken, Gupta, and Rehan (2024): Code & Data","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Chemotherapy-induced cardiotoxicity and mitigation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Code (set theory); Source code; Object code; Software","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":[0.001808807,0.001765602,0.001273446,0.002973649,0.0006841117,0.002470457,0.002833292,0.002774887,0.120965],"category_scores_gemma":[0.01470345,0.0007704925,0.00172508,0.004481425,0.0005330485,0.001504891,0.001998478,0.002071353,0.1213445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001556895,"about_ca_system_score_gemma":0.003138994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02040895,"about_ca_topic_score_gemma":0.0445161,"domain_scores_codex":[0.9986863,0.0002760381,0.0001764411,0.0003278621,0.0003564972,0.0001769817],"domain_scores_gemma":[0.9948421,0.00184874,0.0004982953,0.001181192,0.001156652,0.0004730341],"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":[0.00004995152,0.00001204948,0.0004420967,0.0005136218,0.00002433799,0.0000110555,0.000007607611,0.0001829122,0.00005581297,0.0002661251,0.9970028,0.001431612],"study_design_scores_gemma":[0.0003895206,0.00002385055,0.002865543,0.0004698338,0.00005665853,0.0000661263,0.00003290754,0.0005189056,0.0003185452,0.001985519,0.9932351,0.00003745983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005911205,0.00006811182,0.00009558237,0.0001119468,0.00004389195,0.00001681845,0.9988149,0.0002749628,0.0005146501],"genre_scores_gemma":[0.0003855767,0.00008948525,0.0004699806,0.0001461907,0.00001331383,0.0001197414,0.9977102,0.0001409594,0.0009244931],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.120965,"threshold_uncertainty_score":0.4046683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06055621797297709,"score_gpt":0.3028749458917536,"score_spread":0.2423187279187765,"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."}}