{"id":"W3107682410","doi":"10.18280/isi.250512","title":"Resource Classification and Knowledge Aggregation of Library and Information Based on Data Mining","year":2020,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Resource (disambiguation); Service (business); Big data; Support vector machine; Data mining; Knowledge extraction; Information retrieval; Data science; Database; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001448377,0.0006740768,0.0009591239,0.006005129,0.001177854,0.002599136,0.001389754,0.0006924816,0.000696233],"category_scores_gemma":[0.007159799,0.0002983513,0.001143912,0.006879844,0.0007163624,0.004550237,0.001400248,0.0007629909,0.0002298152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003092138,"about_ca_system_score_gemma":0.001990552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02665449,"about_ca_topic_score_gemma":0.0165026,"domain_scores_codex":[0.9980173,0.0003352502,0.0002246657,0.0005016632,0.0007091442,0.0002119482],"domain_scores_gemma":[0.9975215,0.000915346,0.0004318274,0.0003680918,0.0006362241,0.0001271399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003936279,0.0006078962,0.09571331,0.0005889707,0.0005014262,0.0009684609,0.001378046,0.3059048,0.003704391,0.04186708,0.008063098,0.540309],"study_design_scores_gemma":[0.000006679152,0.00003474217,0.007951514,0.00004031399,0.00008179188,0.0001037581,0.0003772593,0.9694789,0.001945358,0.01762167,0.002334729,0.00002340244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2606097,0.001207665,0.724579,0.001378617,0.0001211851,0.0005335452,0.001314469,0.0009235447,0.009332209],"genre_scores_gemma":[0.9021649,0.0004842958,0.094239,0.00009886377,0.00006482599,0.000186162,0.001147234,0.00002712574,0.001587471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02665449,"threshold_uncertainty_score":0.05299866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03629407125495823,"score_gpt":0.2419431784719548,"score_spread":0.2056491072169966,"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."}}