{"id":"W7117539696","doi":"10.56203/iyd.1801707","title":"ENDÜSTRI ILIŞKILERI IKLIMININ ÇALIŞAN PERFORMANSINA ETKISINDE YÖNETIME GÜVENIN ARACILIK ROLÜ: NEVŞEHIR ILI KAMU ÇALIŞANLARI ÖRNEĞI","year":2025,"lang":"","type":"article","venue":"İzmir Yönetim Dergisi","topic":"Public Relations and Crisis Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Test (biology); Process (computing); Quarter (Canadian coin)","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":[0.002508344,0.0008814104,0.0006552543,0.001225314,0.002112276,0.005723706,0.001176628,0.001395793,0.02997771],"category_scores_gemma":[0.005198992,0.0003582933,0.0008348321,0.001196033,0.001220896,0.002649082,0.002719546,0.001774375,0.007620857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002857545,"about_ca_system_score_gemma":0.004932374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248891,"about_ca_topic_score_gemma":0.01604693,"domain_scores_codex":[0.9972811,0.0005456117,0.0001602649,0.0003515664,0.001228243,0.0004332765],"domain_scores_gemma":[0.9964489,0.0008590601,0.0004277251,0.0002479315,0.001569036,0.0004472963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001508085,0.001196549,0.07431921,0.004999643,0.0002600166,0.00161223,0.02336893,0.006149657,0.02820786,0.04041281,0.04669792,0.7712671],"study_design_scores_gemma":[0.0001016408,0.001549368,0.2215906,0.002885741,0.0003715805,0.001439437,0.05833302,0.008960252,0.02551953,0.02015318,0.658713,0.0003825679],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4855115,0.01283968,0.06107972,0.011342,0.001157232,0.0008543249,0.001825109,0.001956118,0.4234344],"genre_scores_gemma":[0.8363367,0.007506072,0.03603154,0.001068855,0.0002710255,0.000416002,0.001992727,0.0004892669,0.1158879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02997771,"threshold_uncertainty_score":0.1002854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270984389676549,"score_gpt":0.328637932319461,"score_spread":0.3159280884226955,"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."}}