{"id":"W3080377937","doi":"","title":"Victoria's Digital Games Sector Research Report","year":2019,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Face (sociological concept); Government (linguistics); Political science; Public relations; Business; Regional science; Marketing; Geography; Sociology; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004761498,0.0003944983,0.0003260311,0.004641687,0.002275907,0.007459655,0.001100302,0.001372808,0.02501468],"category_scores_gemma":[0.009251477,0.0006402478,0.0003910463,0.007829705,0.0005038742,0.001782785,0.002191521,0.001491978,0.01319962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01862092,"about_ca_system_score_gemma":0.07259673,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6075459,"about_ca_topic_score_gemma":0.5952103,"domain_scores_codex":[0.9944804,0.0005418445,0.0002879167,0.0003543652,0.003526243,0.0008092418],"domain_scores_gemma":[0.9890416,0.001061107,0.000538463,0.0005155145,0.006886426,0.001956808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001484454,0.00009943859,0.01019232,0.0009054069,0.00002726889,0.0001946154,0.001027227,0.0005258122,0.001158169,0.02171694,0.88025,0.08375441],"study_design_scores_gemma":[0.000005795556,0.0000170886,0.01932676,0.0002374628,0.000009710794,0.00005430713,0.0008380539,0.0005278508,0.0004648652,0.0008630249,0.9776358,0.00001933203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03388484,0.01624787,0.003997306,0.03299526,0.002571646,0.001249189,0.171018,0.001218985,0.7368168],"genre_scores_gemma":[0.09922595,0.01388122,0.007766526,0.004010105,0.0002498062,0.0004895412,0.07577448,0.0005779479,0.7980244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6075459,"threshold_uncertainty_score":0.7895308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02013786225775278,"score_gpt":0.2794833442677185,"score_spread":0.2593454820099657,"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."}}