{"id":"W4239826846","doi":"10.32920/ryerson.14654226","title":"#airmaxday2019: Identity and Engagement With Air Max Day 2019 on Twitter","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fandom; Nike; Miami; Social media; Microblogging; Media studies; Advertising; Sociology; Identity (music); Art; Computer science; World Wide Web; Aesthetics; Business","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":[0.0005497304,0.0001997714,0.00016064,0.0006629887,0.002076113,0.002866287,0.0002009923,0.0005318885,0.008074287],"category_scores_gemma":[0.002250074,0.0001076518,0.0001405698,0.0007630236,0.0006825484,0.002740029,0.001750966,0.0005630495,0.001974239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006451925,"about_ca_system_score_gemma":0.0002732513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007133475,"about_ca_topic_score_gemma":0.02013335,"domain_scores_codex":[0.9996821,0.0001258893,0.00001320574,0.00004791688,0.00006449478,0.00006642623],"domain_scores_gemma":[0.99902,0.0003813489,0.0001978557,0.00005382938,0.0001325014,0.0002144834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0006731159,0.0001865355,0.3361639,0.0003674678,0.000048629,0.00102636,0.5494567,0.0001706849,0.008442096,0.006763506,0.03028481,0.06641615],"study_design_scores_gemma":[0.0000155992,0.0001357518,0.3765246,0.0001652809,0.00002486813,0.000338509,0.5246621,0.0008029549,0.001414737,0.0007889702,0.09506994,0.00005659559],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700674,0.0001247001,0.0004068859,0.0009835237,0.00007640222,0.00004099196,0.001007172,0.00003445061,0.02725828],"genre_scores_gemma":[0.9859766,0.0002324569,0.0004419103,0.000270755,0.00005076495,0.00007666295,0.0007452586,0.00005382309,0.01215191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008074287,"threshold_uncertainty_score":0.02701116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018194644451099,"score_gpt":0.321205534922785,"score_spread":0.281023588478274,"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."}}