{"id":"W3145520287","doi":"10.29173/iasl7498","title":"Social Marketing","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Web and Library Services","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social marketing; Public Sector Marketing; Marketing; Public relations; Marketing research; Variety (cybernetics); Government (linguistics); Business; Donation; Marketing management; Marketing science; Return on marketing investment; Business-to-government; Relationship marketing; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00449781,0.0009572268,0.0007747038,0.00277144,0.002595359,0.008002696,0.001128264,0.00290538,0.1995994],"category_scores_gemma":[0.009819715,0.000270628,0.0006417542,0.002795561,0.001897985,0.004619075,0.003320125,0.002624395,0.0574247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002910395,"about_ca_system_score_gemma":0.003545182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804021,"about_ca_topic_score_gemma":0.002329231,"domain_scores_codex":[0.9943045,0.001867006,0.0002818589,0.0006093036,0.002595317,0.0003419767],"domain_scores_gemma":[0.9961609,0.001287145,0.0002809019,0.0004909081,0.001195567,0.000584574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008380334,0.0002176005,0.001139259,0.0007174902,0.0000355336,0.000163976,0.001105408,0.0002013538,0.0006102393,0.1598091,0.2907815,0.5451348],"study_design_scores_gemma":[0.00001154146,0.00005967424,0.0008396714,0.0002732228,0.000006988569,0.0001334402,0.0003764051,0.000116696,0.0001360244,0.01353066,0.9845051,0.00001064978],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002794147,0.009796712,0.008224788,0.01669276,0.002445272,0.0007548824,0.001033714,0.0005962401,0.9576615],"genre_scores_gemma":[0.08674544,0.02770461,0.0136934,0.01769145,0.004071449,0.001578512,0.001866873,0.0004563329,0.8461919],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1995994,"threshold_uncertainty_score":0.6677264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01913831026401826,"score_gpt":0.2418981966871282,"score_spread":0.2227598864231099,"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."}}