{"id":"W3085388717","doi":"","title":"PENGELOLAAN DATA PENELITIAN DI PERPUSTAKAAN: TANTANGAN DAN PERSIAPANNYA BAGI PUSTAKAWAN","year":2020,"lang":"id","type":"article","venue":"VISI PUSTAKA Buletin Jaringan Informasi Antar Perpustakaan","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data management; Research data; Competence (human resources); Digital library; Service (business); Library science; Knowledge management; Computer science; Business; World Wide Web; Data curation; Management; Marketing; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002349558,0.000546131,0.0006525179,0.0021484,0.002585749,0.01006223,0.0007173602,0.0007588306,0.03285451],"category_scores_gemma":[0.004260493,0.0005668384,0.0004312546,0.007034198,0.001343932,0.008418771,0.003019806,0.001934206,0.01114859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001772284,"about_ca_system_score_gemma":0.005450676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004762978,"about_ca_topic_score_gemma":0.004015046,"domain_scores_codex":[0.9982733,0.0003534689,0.0002571423,0.0003206316,0.000640984,0.0001544741],"domain_scores_gemma":[0.9966872,0.001254241,0.0002736618,0.0005162312,0.0009758176,0.0002928256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005712751,0.000317448,0.01442208,0.002510049,0.00007446403,0.002629803,0.02194825,0.0008244,0.003660504,0.0682501,0.1403741,0.7444175],"study_design_scores_gemma":[0.00001973865,0.00006330113,0.0064522,0.0005091625,0.00003796541,0.001138461,0.009252562,0.0006263453,0.002950534,0.00684174,0.9720547,0.00005340243],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2003148,0.03436377,0.04978037,0.03610933,0.007828245,0.0006140556,0.01617917,0.004505238,0.650305],"genre_scores_gemma":[0.586257,0.0344102,0.0630175,0.002914249,0.001412999,0.0008115952,0.0138294,0.001558494,0.2957886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9899378,"threshold_uncertainty_score":0.1099094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06702623326598389,"score_gpt":0.2665704508645598,"score_spread":0.1995442175985759,"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."}}