{"id":"W4393144880","doi":"10.32920/25475137.v1","title":"Sustainable fashion social media influencers and content creation calibration","year":2024,"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; Content (measure theory); Social media; Calibration; Business; Sustainable development; Computer science; Marketing; World Wide Web; Political science; Mathematics; Statistics","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":[0.01356089,0.0004218022,0.0002176432,0.002544528,0.002048695,0.007734111,0.0009228719,0.001172482,0.007168549],"category_scores_gemma":[0.06484297,0.0004558529,0.0003753014,0.002132622,0.01046847,0.007513151,0.005093795,0.001336385,0.0008729143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003845047,"about_ca_system_score_gemma":0.002586487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170698,"about_ca_topic_score_gemma":0.001885902,"domain_scores_codex":[0.9842173,0.01027734,0.0005077337,0.001323724,0.002979572,0.0006944345],"domain_scores_gemma":[0.913668,0.05946995,0.00989507,0.009040513,0.006090852,0.001835608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002447371,0.0005762874,0.1636098,0.0005600389,0.0001062486,0.001112183,0.2286217,0.002051909,0.006755932,0.3412214,0.004965916,0.2501737],"study_design_scores_gemma":[0.0001106687,0.0003840122,0.2700272,0.0011032,0.0001675108,0.001793341,0.1940661,0.01475688,0.0225627,0.3037538,0.1910132,0.0002614142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6817034,0.001003183,0.04018348,0.006589471,0.0001181303,0.0004249912,0.0001765075,0.0003394457,0.2694613],"genre_scores_gemma":[0.9927347,0.0002202161,0.003445813,0.0001643804,0.00003200232,0.00007586572,0.00004797713,0.00006679782,0.00321232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01356089,"threshold_uncertainty_score":0.07171768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03689989984644369,"score_gpt":0.304497539341433,"score_spread":0.2675976394949893,"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."}}