{"id":"W3107592974","doi":"10.23889/ijpds.v5i3.1369","title":"Impact through Engagement","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Queen's University; Ulster University; Queen's University Belfast; Health and Social Care Northern Ireland; UK Research and Innovation","keywords":"Public engagement; General partnership; Publics; Public relations; Work (physics); Key (lock); Community engagement; Business; Political science; Knowledge management; Computer science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.005096086,0.0000997204,0.0001294005,0.0002576902,0.0005261045,0.001557961,0.004199477,0.00002581902,0.000282916],"category_scores_gemma":[0.008333358,0.00007062548,0.0001050103,0.0008136348,0.00009902214,0.005203754,0.0004431965,0.0001522805,0.0000754911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007320975,"about_ca_system_score_gemma":0.000176662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006152542,"about_ca_topic_score_gemma":0.000008624264,"domain_scores_codex":[0.995339,0.00006745777,0.0007128512,0.0005415028,0.003121188,0.0002179834],"domain_scores_gemma":[0.9971684,0.0003113193,0.0004639093,0.0004601449,0.001401251,0.0001949325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006476931,0.0002663375,0.2426414,0.000005778903,0.0002003095,0.00002778665,0.00428444,0.1063574,0.005488085,0.05699373,0.1066406,0.4764464],"study_design_scores_gemma":[0.0007542807,0.0001570116,0.09699062,0.00001600787,0.00001713119,0.00005105095,0.0006621483,0.7754239,0.00005000569,0.05863683,0.06702655,0.0002144545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3571129,0.00004729986,0.6259856,0.01187531,0.003500433,0.0001978979,0.0004271822,0.00004499678,0.0008084681],"genre_scores_gemma":[0.9811763,0.00003629689,0.01701493,0.001025777,0.0005309057,0.00000240294,0.000159887,0.000006456413,0.00004709532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6690665,"threshold_uncertainty_score":0.9994785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5733097696198401,"score_gpt":0.5698511322761074,"score_spread":0.003458637343732751,"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."}}