{"id":"W4292337426","doi":"10.1787/08f79edd-en","title":"Co-creation during COVID-19","year":2022,"lang":"en","type":"paratext","venue":"OECD science, technology and industry policy papers","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Queensland; Agencia Nacional de Investigación y Desarrollo; Ministry of Education, Culture, Sports, Science and Technology; RIKEN; Vlaamse regering; European Commission; Government of Canada; Australian Government; Commonwealth Scientific and Industrial Research Organisation; Innovation, Science and Economic Development Canada","keywords":"Coronavirus disease 2019 (COVID-19); Government (linguistics); Pandemic; Co-creation; Key (lock); Civil society; Process (computing); Political science; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public relations; Business; Knowledge management; Marketing; Computer science; Politics; Medicine; Computer security","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03264093,0.0005504728,0.0005326558,0.00330572,0.01237551,0.01297462,0.001834713,0.002727067,0.005347736],"category_scores_gemma":[0.03837063,0.0005263286,0.0007662668,0.005498993,0.01531282,0.007278775,0.03036797,0.005317827,0.0008957065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01286389,"about_ca_system_score_gemma":0.02138135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007855718,"about_ca_topic_score_gemma":0.01200628,"domain_scores_codex":[0.9655848,0.01806647,0.001482254,0.002332967,0.005116067,0.007417483],"domain_scores_gemma":[0.9479289,0.02472911,0.004765403,0.008094313,0.005759758,0.008722575],"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":[0.0002084952,0.0002379435,0.02046597,0.0006126859,0.00003654635,0.003021348,0.1635071,0.001122116,0.001759753,0.6707969,0.01815207,0.120079],"study_design_scores_gemma":[0.00005580649,0.0002784341,0.01509858,0.000862308,0.00002275192,0.001587205,0.1279469,0.0007849263,0.002246977,0.04432806,0.8066766,0.0001114217],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.4003282,0.002498376,0.0245379,0.01269943,0.0009401821,0.001874662,0.0005513021,0.0002935069,0.5562764],"genre_scores_gemma":[0.9632654,0.0005141548,0.006995964,0.001506043,0.00009944417,0.0008190144,0.000275617,0.0001012739,0.02642308],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03264093,"threshold_uncertainty_score":0.1726238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384296910265509,"score_gpt":0.3174744231388481,"score_spread":0.293631454036193,"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."}}