{"id":"W4210879327","doi":"10.1111/1468-229x.13259","title":"Out of the Ivory Tower, into the Digital World? Democratising Scholarly Exchange","year":2022,"lang":"en","type":"article","venue":"History","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Ivory tower; Media studies; Event (particle physics); Digital media; Public relations; Public engagement; Political science; Sociology; Reflection (computer programming); Computer science; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.02053393,0.0003459016,0.0003692654,0.002090412,0.01621187,0.02704568,0.00163275,0.004004175,0.02114881],"category_scores_gemma":[0.02666322,0.0002952013,0.0003210476,0.002130499,0.03351376,0.03275149,0.02945819,0.005463406,0.00200049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006598971,"about_ca_system_score_gemma":0.006707942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002084349,"about_ca_topic_score_gemma":0.002924935,"domain_scores_codex":[0.9821185,0.01377213,0.0003466639,0.0008729699,0.001183432,0.001706283],"domain_scores_gemma":[0.9771224,0.01460206,0.001513228,0.003152504,0.000727224,0.002882545],"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":[0.00005992115,0.00006905464,0.001179339,0.0001275443,0.000008960549,0.0003065842,0.1147274,0.000338928,0.0003293122,0.8395216,0.01227141,0.03106003],"study_design_scores_gemma":[0.0000366282,0.00005602701,0.001071933,0.0008713665,0.000008600365,0.0002248228,0.1805841,0.000739839,0.0004911954,0.3333514,0.4825314,0.00003258649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2078515,0.007976036,0.01937125,0.1657605,0.001804414,0.0001216777,0.00006918747,0.0002250278,0.5968204],"genre_scores_gemma":[0.9804162,0.001056521,0.002076205,0.003872883,0.0003092989,0.00005708832,0.00002083639,0.00006880139,0.01212216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9983672,"threshold_uncertainty_score":0.1085951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02801560196877416,"score_gpt":0.2159326017110189,"score_spread":0.1879169997422447,"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."}}