{"id":"W4200546404","doi":"10.29173/iq1025","title":"IASSIST gone glocal","year":2021,"lang":"en","type":"article","venue":"IASSIST Quarterly","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glocalization; Acronym; Framing (construction); Documentation; Political science; Media studies; History; Law; Sociology; Linguistics; Globalization","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002194768,0.0001830937,0.0003572752,0.0001352239,0.0002389049,0.001017836,0.0009305836,0.00008401769,0.002731413],"category_scores_gemma":[0.0006571875,0.0001508922,0.0002178618,0.0008987173,0.0001547429,0.0005279186,0.0001506991,0.0001583882,0.00626774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005515925,"about_ca_system_score_gemma":0.0001144132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008941768,"about_ca_topic_score_gemma":0.0008979169,"domain_scores_codex":[0.9960198,0.0004481938,0.0007872719,0.0007894814,0.001560777,0.0003945227],"domain_scores_gemma":[0.9972551,0.0005357211,0.0001861437,0.001517972,0.0002894622,0.0002155265],"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":[0.00002542528,0.0003099881,0.0005523408,0.00001117528,0.00004902541,0.0002798401,0.0009453797,0.000003275603,0.0004573573,0.03593353,0.2425148,0.7189179],"study_design_scores_gemma":[0.0005397204,0.0001932602,0.04031278,0.00001967388,0.0000308931,0.00003275872,0.008048995,0.0002183005,0.0004130226,0.02913447,0.9207348,0.0003213627],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2754123,0.001412666,0.2107777,0.07025928,0.008599614,0.0006887374,0.0007241899,0.0007301054,0.4313954],"genre_scores_gemma":[0.9656522,0.000005536094,0.001645294,0.002705571,0.000249008,0.00002019246,0.0000691452,0.00001518599,0.02963792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7185965,"threshold_uncertainty_score":0.9981802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1565385725467741,"score_gpt":0.419423647592809,"score_spread":0.2628850750460349,"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."}}