{"id":"W1502332670","doi":"10.22230/src.2014v5n3a162","title":"Knowledge Co-Creation and Assistive Technology","year":2014,"lang":"en","type":"article","venue":"Scholarly and Research Communication","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Praxis; Scholarship; Knowledge management; Service (business); Knowledge transfer; Knowledge production; Perspective (graphical); Co-creation; Consumption (sociology); Production (economics); Computer science; Sociology; Business; Political science; Social science; Artificial intelligence; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01103282,0.0006275301,0.0005226496,0.003137926,0.009680698,0.0179652,0.002104819,0.003569094,0.006166455],"category_scores_gemma":[0.01538384,0.000316707,0.0003962589,0.00288975,0.04711074,0.0110941,0.01968539,0.003153501,0.0007843149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00412863,"about_ca_system_score_gemma":0.007640944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00165459,"about_ca_topic_score_gemma":0.001904367,"domain_scores_codex":[0.9819916,0.01215194,0.0003608179,0.001343228,0.00235894,0.001793548],"domain_scores_gemma":[0.9753068,0.01704359,0.001459389,0.003447343,0.001332952,0.00140989],"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":[0.000049553,0.0001095799,0.002110387,0.0001716244,0.00001683565,0.0007572104,0.192753,0.0004654317,0.0007755875,0.7612,0.001777306,0.03981354],"study_design_scores_gemma":[0.00004766629,0.0001719035,0.001938344,0.000487611,0.00001973501,0.001968514,0.2235286,0.002289998,0.003120289,0.5393979,0.2269771,0.00005241597],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3206258,0.004752728,0.05684339,0.03243379,0.0004368395,0.0002116473,0.00003341129,0.0002292527,0.5844331],"genre_scores_gemma":[0.9846523,0.0005986117,0.003109447,0.0003955514,0.0001033097,0.00007152309,0.000008842283,0.00004258994,0.01101771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0179652,"threshold_uncertainty_score":0.05834782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06075506679856065,"score_gpt":0.4278842571124599,"score_spread":0.3671291903138993,"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."}}