{"id":"W2603402957","doi":"10.1332/174426416x14614935571225","title":"Information into knowledge: navigating the complexity in the campus community engagement context","year":2016,"lang":"en","type":"article","venue":"Evidence & Policy","topic":"Service-Learning and Community Engagement","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Knowledge management; Key (lock); Context (archaeology); Community engagement; Process (computing); Computer science; Data science; Public relations; Psychology; Political science; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.01304848,0.0005662479,0.0008723061,0.005981827,0.01414017,0.03356344,0.002690729,0.006371976,0.008613023],"category_scores_gemma":[0.03056837,0.0007645105,0.0008527361,0.006593312,0.04190293,0.04378567,0.02666879,0.005731537,0.0008763244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007080977,"about_ca_system_score_gemma":0.009373416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008975669,"about_ca_topic_score_gemma":0.00690222,"domain_scores_codex":[0.9762515,0.01839776,0.0006641725,0.001130079,0.002054066,0.001502463],"domain_scores_gemma":[0.9570909,0.03625238,0.00150314,0.002445229,0.001392974,0.001315268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008541733,0.000102995,0.005855876,0.0007361156,0.00003775374,0.002594571,0.442889,0.001655992,0.001185941,0.4814216,0.002325787,0.061109],"study_design_scores_gemma":[0.00002802043,0.00007956513,0.002251917,0.0008472843,0.00003249404,0.001221443,0.4739774,0.002175104,0.001286122,0.3422972,0.1757403,0.00006312352],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4061293,0.004717323,0.140626,0.09106191,0.0003241082,0.0007083999,0.0002940714,0.0002906954,0.3558483],"genre_scores_gemma":[0.9779134,0.001313144,0.01482786,0.001003939,0.00006210295,0.0001853496,0.00008231525,0.00008108948,0.004530773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03356344,"threshold_uncertainty_score":0.06900781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2140720243107957,"score_gpt":0.4277075607680591,"score_spread":0.2136355364572634,"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."}}