{"id":"W7145227745","doi":"","title":"つながる人とデータ : IFLA WLIC 2013におけるLinked Dataとコミュニティ活動","year":2014,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nutrasource","funders":"","keywords":"Variety (cybernetics); Work (physics); Workflow; Information system","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.00181009,0.0006684846,0.0006419229,0.0004203081,0.002112772,0.003282997,0.003860057,0.000297367,0.0002046694],"category_scores_gemma":[0.0007851637,0.0006138316,0.0002487077,0.001663975,0.001028285,0.02925082,0.001967816,0.0006263127,0.004060465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002549968,"about_ca_system_score_gemma":0.001754531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006547931,"about_ca_topic_score_gemma":0.00002450034,"domain_scores_codex":[0.9930853,0.0003690277,0.001725473,0.001366034,0.002417191,0.00103696],"domain_scores_gemma":[0.9943717,0.0003821844,0.0007806692,0.003111743,0.0006072934,0.0007464073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000104423,0.0004014783,0.004002002,0.00043854,0.0001760103,0.0001956972,0.004561274,0.001185686,0.003494689,0.8020639,0.1756143,0.007761973],"study_design_scores_gemma":[0.0008666301,0.0001936853,0.002618405,0.0004891478,0.00002136839,0.0005463479,0.0002593205,0.0587175,0.00347973,0.0003971531,0.931531,0.0008796758],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07637109,0.002344425,0.6326019,0.00934623,0.07814291,0.002189003,0.002959387,0.001629837,0.1944152],"genre_scores_gemma":[0.9701902,0.000197259,0.01145748,0.003100827,0.006505184,0.0000830033,0.002066253,0.00003541575,0.00636437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8938191,"threshold_uncertainty_score":0.9996313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0212084569771399,"score_gpt":0.2398786009413462,"score_spread":0.2186701439642063,"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."}}