{"id":"W3211231734","doi":"10.5281/zenodo.4084763","title":"Data Repository Selection: Criteria That Matter","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Victoria Park","funders":"","keywords":"Selection (genetic algorithm); Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002508949,0.00008827876,0.00008183729,0.00005340057,0.00146891,0.001729557,0.003337392,0.00003004673,0.002912862],"category_scores_gemma":[0.00008496603,0.00009347293,0.00001818155,0.0004940759,0.00005597854,0.0008264436,0.003520569,0.0001576834,0.008910786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002997714,"about_ca_system_score_gemma":0.000003548906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007632374,"about_ca_topic_score_gemma":4.435397e-8,"domain_scores_codex":[0.9987137,0.0001273808,0.000149047,0.0005715298,0.0002340378,0.0002043252],"domain_scores_gemma":[0.9986779,0.00001179183,0.00006459477,0.0009140088,0.0001651965,0.0001665195],"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":[0.000004259431,0.00003812461,0.000006239599,0.00001677238,0.00001364208,0.000006201525,0.0005321258,0.000004080396,0.002523976,0.002938193,0.9387698,0.05514665],"study_design_scores_gemma":[0.0001193496,0.00005485272,0.0004963978,0.000006590039,0.00000440746,0.000118231,0.00005074942,0.0330402,0.000473663,0.00005684506,0.965468,0.0001107329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000951833,0.00005397849,0.8845112,0.0130822,0.0001691152,0.0003086358,0.0005524274,0.001902925,0.09846772],"genre_scores_gemma":[0.8254454,0.00009104335,0.1440085,0.009271407,0.002062213,3.205747e-7,0.01216572,0.002769849,0.004185557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8244935,"threshold_uncertainty_score":0.999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09740853218669542,"score_gpt":0.2794724886981486,"score_spread":0.1820639565114532,"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."}}