{"id":"W2601916917","doi":"10.1080/15295036.2017.1304648","title":"When paratexts become texts: de-centering the game-as-text","year":2017,"lang":"en","type":"article","venue":"Critical Studies in Media Communication","topic":"Digital Games and Media","field":"Social Sciences","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Sociology; Fandom; Paratext; Media studies; Advertising; Linguistics; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.001424451,0.00009583597,0.0001823046,0.00002511881,0.0009558588,0.0002998861,0.001397313,0.00007187301,0.00006955076],"category_scores_gemma":[0.01762042,0.00007394265,0.00004814363,0.00005482796,0.003252501,0.0003802892,0.0006462085,0.0002695482,0.0001071194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000177456,"about_ca_system_score_gemma":0.000069791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003731652,"about_ca_topic_score_gemma":0.005329211,"domain_scores_codex":[0.9986581,0.0003084909,0.0002256919,0.0001451877,0.0002795858,0.0003829849],"domain_scores_gemma":[0.9966289,0.002214169,0.00006652785,0.0008365098,0.0001379673,0.0001159221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002786298,0.0002236499,0.008606104,0.00005374886,0.00004586646,0.00001506397,0.2453279,0.000001457599,0.00002461558,0.3577866,0.005206179,0.382681],"study_design_scores_gemma":[0.0003733097,0.00003213682,0.01998938,0.0003782632,0.00002492833,0.00000213152,0.05587618,0.00004334102,0.00002392516,0.1312895,0.7917595,0.0002073845],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2018656,0.01956677,0.00005366651,0.1413396,0.001601719,0.0005740196,0.000007884277,0.00009529822,0.6348954],"genre_scores_gemma":[0.9862432,0.01125605,0.000352194,0.0007039463,0.0001681728,0.0001086298,0.000002455601,0.000008601482,0.001156683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7865533,"threshold_uncertainty_score":0.9994601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1244743406055823,"score_gpt":0.4456233032268349,"score_spread":0.3211489626212526,"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."}}