{"id":"W4288060670","doi":"10.18357/kula.171","title":"Leveraging Wikidata to Build Scholarly Profiles as Service","year":2022,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Service (business); World Wide Web; Work (physics); Focus (optics); Scholarly communication; Computer science; Data science; Service model; Knowledge management; Library science; Sociology; Political science; Business; Engineering; Marketing; Publishing","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0118359,0.0009817161,0.0006189069,0.009255189,0.003617699,0.0131426,0.002600876,0.001821459,0.003476678],"category_scores_gemma":[0.04008591,0.0007759313,0.001051388,0.00632444,0.002521994,0.02712147,0.01651082,0.004151859,0.004909092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001350283,"about_ca_system_score_gemma":0.005504349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002776812,"about_ca_topic_score_gemma":0.005157543,"domain_scores_codex":[0.9911965,0.00342548,0.001157644,0.0009399878,0.002899583,0.00038092],"domain_scores_gemma":[0.959612,0.01555761,0.002255206,0.01388984,0.004793822,0.003891607],"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":[0.0001940869,0.0006382645,0.007556299,0.001255977,0.000167546,0.001171825,0.03305915,0.002994018,0.009359744,0.1453918,0.03847412,0.7597371],"study_design_scores_gemma":[0.00006285236,0.0001647239,0.001928724,0.00069432,0.00008492951,0.0009986487,0.009839705,0.03038016,0.01599093,0.1149706,0.8246133,0.0002711502],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03679787,0.0009775411,0.8511688,0.008399175,0.001595352,0.001519375,0.001193459,0.03636214,0.06198623],"genre_scores_gemma":[0.1311612,0.001132432,0.832187,0.001100763,0.0005220873,0.001148031,0.003813628,0.003967391,0.02496748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9868574,"threshold_uncertainty_score":0.06259501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07245173051620885,"score_gpt":0.437358537660259,"score_spread":0.3649068071440501,"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."}}