{"id":"W6894289743","doi":"10.5281/zenodo.8091612","title":"Collecting Digital Object Reuse Data and Assessing it with Care","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reuse; Documentation; Relevance (law); Process (computing); Presentation (obstetrics); Best practice; Work (physics)","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":[0.1738307,0.0008972568,0.001233723,0.01815605,0.005825643,0.01626411,0.004803145,0.002300705,0.004958075],"category_scores_gemma":[0.2875809,0.001044767,0.001434214,0.01587182,0.009663401,0.01708062,0.02091747,0.004313885,0.002645385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0171569,"about_ca_system_score_gemma":0.03836085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03043227,"about_ca_topic_score_gemma":0.03101143,"domain_scores_codex":[0.7391972,0.1412759,0.02582123,0.008158961,0.08197387,0.003572966],"domain_scores_gemma":[0.6882687,0.1255644,0.02739949,0.07580329,0.07765775,0.005306371],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001209483,0.0002391018,0.04323122,0.003012023,0.0001261317,0.0003224685,0.06372251,0.001186242,0.002093666,0.09922232,0.04145946,0.7452639],"study_design_scores_gemma":[0.00009462373,0.0004309039,0.05935858,0.01218462,0.0002158214,0.000843409,0.07934782,0.004686703,0.01158559,0.2043214,0.6265292,0.0004013774],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0841778,0.006024008,0.6529145,0.0982116,0.0008640728,0.01200198,0.008243636,0.003896585,0.1336658],"genre_scores_gemma":[0.2062867,0.004818166,0.7595478,0.004763436,0.0002183692,0.008948148,0.005522266,0.0008651068,0.009029953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8261693,"threshold_uncertainty_score":0.9193157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1538870931034939,"score_gpt":0.3418202060478416,"score_spread":0.1879331129443477,"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."}}