{"id":"W4292843507","doi":"10.3102/1435173","title":"Reading Images: Becoming Media Critical in a Foreign Culture in the Post-Truth Era","year":2019,"lang":"en","type":"article","venue":"Proceedings of the 2019 AERA Annual Meeting","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Canada","keywords":"Reading (process); Computer science; Artificial intelligence; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002893579,0.000119183,0.0002221482,0.00006905415,0.0003414,0.00008676745,0.001009763,0.00009957504,0.00001444774],"category_scores_gemma":[0.0064696,0.00007454775,0.00007545551,0.0004722338,0.0002066564,0.0004402542,0.0002695119,0.0004567223,0.00001030496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007717416,"about_ca_system_score_gemma":0.00004728116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001617279,"about_ca_topic_score_gemma":0.0002801914,"domain_scores_codex":[0.9984977,0.00009308662,0.0003417948,0.0002027666,0.000474399,0.0003902371],"domain_scores_gemma":[0.9981885,0.001117577,0.0001722382,0.0001401259,0.0003432517,0.00003829111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005345735,0.0001091201,0.1673437,0.0001261416,0.00001344712,6.757946e-7,0.6086086,0.000003810206,0.004566752,0.2141964,0.003044942,0.001933004],"study_design_scores_gemma":[0.000544893,0.00007743136,0.04454984,0.001126105,0.00002663471,0.000003266429,0.9354127,0.00009246871,0.0009884824,0.01347875,0.00341301,0.0002864088],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8768273,0.0003967107,2.958923e-7,0.01082425,0.0002455114,0.0004215817,0.00000756112,0.00001854073,0.1112582],"genre_scores_gemma":[0.9985413,0.0001959692,0.0005457487,0.0003742823,0.0001809134,0.00002500779,0.000001187388,0.000009892055,0.0001257106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3268041,"threshold_uncertainty_score":0.7745183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410678988179031,"score_gpt":0.2934969644165106,"score_spread":0.2793901745347203,"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."}}