{"id":"W4393720819","doi":"10.5281/zenodo.7853026","title":"Dataset Citation and Re-use Data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Citation; Data science; Information retrieval; Computer science; Geography; Library science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001610518,0.001547035,0.001345665,0.01152004,0.001053405,0.002887235,0.002498574,0.002383056,0.04145849],"category_scores_gemma":[0.01254987,0.0004253511,0.001196581,0.02085523,0.0004748472,0.001482049,0.001846035,0.001999009,0.05658468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001710739,"about_ca_system_score_gemma":0.003037262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0153997,"about_ca_topic_score_gemma":0.02635628,"domain_scores_codex":[0.9971269,0.0004117035,0.0005350136,0.0006803322,0.0009089724,0.0003371117],"domain_scores_gemma":[0.9918935,0.002343345,0.001015594,0.001752895,0.002555754,0.0004390028],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007238943,0.00004870515,0.002179362,0.0007115603,0.00004651415,0.00006076873,0.00005861811,0.0005181263,0.0002286537,0.001505982,0.9897626,0.004806664],"study_design_scores_gemma":[0.0001128309,0.00001916853,0.007121467,0.0002710361,0.00003190101,0.000113355,0.0001327658,0.0004020115,0.0004260794,0.0014364,0.9898986,0.00003432258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004581443,0.00008929968,0.00006470567,0.0000837367,0.00003765806,0.00001323115,0.9983273,0.000134515,0.0007914514],"genre_scores_gemma":[0.0005911217,0.00005957721,0.0002121251,0.00003165033,0.00001307438,0.00006324433,0.9981951,0.00003564082,0.0007983472],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9983895,"threshold_uncertainty_score":0.1386924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486725176998717,"score_gpt":0.3383325486324027,"score_spread":0.189660030932531,"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."}}