{"id":"W4236956964","doi":"10.32920/14652858","title":"Examining factors that predict user engagement on YouTube","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Influencer marketing; User engagement; Social media; Advertising; Channel (broadcasting); Social media marketing; Psychology; Social engagement; Internet privacy; Computer science; Business; Sociology; World Wide Web; Marketing","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":[0.001078337,0.0005451143,0.0003418698,0.001778849,0.0004870723,0.001468177,0.0002944211,0.0006628307,0.005501431],"category_scores_gemma":[0.008289728,0.0001796023,0.0007000343,0.001288077,0.0003620785,0.001274948,0.0007927782,0.0006348983,0.001108787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006793134,"about_ca_system_score_gemma":0.0007072254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01807449,"about_ca_topic_score_gemma":0.01590964,"domain_scores_codex":[0.9993193,0.0002380261,0.00005000235,0.00009033935,0.0001505774,0.0001517359],"domain_scores_gemma":[0.9940031,0.004009516,0.0007830026,0.0001594897,0.0005595756,0.0004852922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008833071,0.0001932106,0.9889082,0.00002525143,0.00004794481,0.00005160093,0.0005361807,0.0009333423,0.000287634,0.0002846335,0.0003171309,0.008326491],"study_design_scores_gemma":[0.00001258453,0.0002664742,0.9455117,0.00004286088,0.00006536974,0.00007224386,0.002601227,0.04932244,0.0004350643,0.0006678391,0.000980677,0.0000214661],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991828,0.00008266579,0.002419519,0.0002416762,0.000008894176,0.00009052407,0.0005245248,0.00003835414,0.004765906],"genre_scores_gemma":[0.9976205,0.00005933607,0.0007813084,0.00001600931,0.000007120446,0.00006325539,0.0005132376,0.000005593323,0.0009337381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01807449,"threshold_uncertainty_score":0.03593856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1575492777984633,"score_gpt":0.32894921339772,"score_spread":0.1713999355992567,"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."}}