{"id":"W6980409602","doi":"","title":"Capitalizing on Big Data: Toward a Policy Framework and Advancing Digital Scholarship in Canada: Consultation Document","year":2018,"lang":"en","type":"other","venue":"QSpace (Queen's University Library)","topic":"Information Systems Education and Curriculum Development","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Genome Canada","keywords":"Digital ecosystem; Scholarship; Digital scholarship; Key (lock); Big data; Digital economy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007236455,0.0002440865,0.0002374714,0.0007389691,0.00009965096,0.000404845,0.0009316098,0.0001483745,0.00009146514],"category_scores_gemma":[0.00009806098,0.0002667038,0.00002008668,0.0007506286,0.00003867788,0.002626182,0.0006395918,0.0002280435,0.00009654149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007855709,"about_ca_system_score_gemma":0.003838767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3962457,"about_ca_topic_score_gemma":0.05028251,"domain_scores_codex":[0.9985694,0.00007743067,0.0001984967,0.0004726196,0.0003719296,0.000310088],"domain_scores_gemma":[0.9987971,0.00008513987,0.0002806355,0.0005974445,0.000036742,0.0002029002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009701765,0.00002501775,0.006681918,0.0001279996,0.00004663216,0.00004240168,0.002924119,0.00000783168,3.910174e-8,0.02855034,0.954834,0.006750021],"study_design_scores_gemma":[0.0003276214,0.00002133845,0.00321977,0.0006814651,0.000004111254,0.000001340127,0.002865911,0.00002349818,0.00001154738,0.0002261518,0.9922196,0.0003976566],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00678979,0.0001439159,0.05875842,0.1129104,0.005068783,0.002401898,0.0004239618,0.001168194,0.8123346],"genre_scores_gemma":[0.1801901,0.0004494107,0.03196893,0.002290558,0.0007325491,0.00000609145,0.0005397871,0.0001818723,0.7836407],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3459632,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386417925962277,"score_gpt":0.2148521907942935,"score_spread":0.2009880115346707,"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."}}