{"id":"W2896947944","doi":"10.17831/rep:arcc%y464","title":"Japan-ness + Gaijin-ness","year":2018,"lang":"en","type":"article","venue":"ARCC Conference Repository (Architectural Research Centers Consortium)","topic":"Japanese History and Culture","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.002347636,0.0003725513,0.0004354069,0.0003745002,0.004496644,0.0005788154,0.001566287,0.0002952951,0.001030223],"category_scores_gemma":[0.001036182,0.0003293483,0.0002288498,0.0009498839,0.007028151,0.0004754889,0.0003414383,0.001235357,0.0005318976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005190224,"about_ca_system_score_gemma":0.001493596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004446873,"about_ca_topic_score_gemma":0.004967702,"domain_scores_codex":[0.9917014,0.002607389,0.000557558,0.001003141,0.002263038,0.001867495],"domain_scores_gemma":[0.9956737,0.0005745942,0.0001734529,0.0008349857,0.001839759,0.0009035229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002759768,0.001045001,0.1042246,0.0003922976,0.0005663222,0.0009001789,0.3540202,0.00001347554,0.2569391,0.1093444,0.02797082,0.1418239],"study_design_scores_gemma":[0.002474282,0.001387855,0.06122504,0.0009124958,0.0001028841,0.0003842626,0.0723946,0.0002610012,0.03065654,0.00592359,0.8218869,0.002390573],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8023967,0.0002080886,0.00007810912,0.001852445,0.001621858,0.0006978423,0.00001046858,0.000247803,0.1928867],"genre_scores_gemma":[0.9697759,0.00005020784,0.0000911358,0.0001903038,0.00135438,0.0001056998,0.0000122966,0.00003565431,0.02838438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.793916,"threshold_uncertainty_score":0.9999158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0780925818108165,"score_gpt":0.3726607117110379,"score_spread":0.2945681299002214,"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."}}