{"id":"W4253435963","doi":"10.32920/ryerson.14654355","title":"Instagram, influencers, and native advertising: examining follower engagement with influencer content","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Digital Communication and Language","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Professional Engineers Ontario","funders":"","keywords":"Influencer marketing; Advertising; Context (archaeology); Commission; Social media; Product (mathematics); Business; Content analysis; Marketing; Political science; Sociology; Relationship marketing; Marketing management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003566408,0.0003113245,0.0003270207,0.0001445168,0.0001421345,0.00128721,0.001193768,0.0001179203,0.00004860801],"category_scores_gemma":[0.000102133,0.0002436561,0.00005484251,0.0002510574,0.000133507,0.0008155631,0.00449143,0.0006220762,0.000004405015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083736,"about_ca_system_score_gemma":0.0002932714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003009277,"about_ca_topic_score_gemma":0.0001661599,"domain_scores_codex":[0.9980804,0.0001712134,0.0003383744,0.000699891,0.0004489158,0.0002612147],"domain_scores_gemma":[0.9978883,0.000147493,0.0002031547,0.001346391,0.0002668041,0.0001478276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001240938,0.001086243,0.04086831,0.000752212,0.00218049,0.0009307212,0.111928,0.003169646,0.001911934,0.3994223,0.0007360864,0.43689],"study_design_scores_gemma":[0.01371545,0.003284269,0.634141,0.01280843,0.0005043651,0.0003630274,0.09732705,0.03372596,0.01740683,0.006514862,0.1668794,0.0133294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6655959,0.002172453,0.1010096,0.0007746436,0.0002008794,0.0007163949,0.000005861247,0.0004361939,0.2290881],"genre_scores_gemma":[0.9595401,0.0001130146,0.03701437,0.002127283,0.000007444584,0.00007079245,0.00001834263,0.00001480876,0.001093873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5932727,"threshold_uncertainty_score":0.9997495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07409199491177025,"score_gpt":0.278506255433599,"score_spread":0.2044142605218288,"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."}}