{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001998391,0.0001882562,0.0002980423,0.001240527,0.001199997,0.003006832,0.0003210877,0.0004850345,0.003529993],"category_scores_gemma":[0.00989071,0.0002037321,0.0002539786,0.0007950774,0.0008938956,0.001526989,0.001883372,0.0007295499,0.000573124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000690372,"about_ca_system_score_gemma":0.0006696465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003844504,"about_ca_topic_score_gemma":0.006258006,"domain_scores_codex":[0.9984537,0.0005834037,0.0000951301,0.0001527069,0.0004791055,0.0002359924],"domain_scores_gemma":[0.9878119,0.006826777,0.002975425,0.0005256926,0.0008931849,0.000966994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002952821,0.0007321647,0.7366968,0.0001478227,0.00004530699,0.0002785103,0.2070158,0.00004524079,0.003293918,0.001236734,0.0006248973,0.04958743],"study_design_scores_gemma":[0.000008102687,0.0004276793,0.8623232,0.00004915093,0.00003266997,0.0002524259,0.1304684,0.0003109908,0.001029054,0.0002391717,0.004840844,0.00001827505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964251,0.000049112,0.00009557152,0.00005694007,0.000003500532,0.00001370048,0.00002129305,0.000002846615,0.003331929],"genre_scores_gemma":[0.9971228,0.0001151474,0.0002738101,0.00006042671,0.00001431456,0.00003628461,0.00004473247,0.000005745256,0.002326671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003844504,"threshold_uncertainty_score":0.01180899,"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."}}