{"id":"W7008840542","doi":"","title":"Dark future at work : scale adaptation and validation","year":2024,"lang":"en","type":"article","venue":"Saint Mary's University Institutional Repository (Saint Mary's University)","topic":"Technostress in Professional Settings","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greenfield Research (Canada)","funders":"","keywords":"Scale (ratio); Work (physics); Adaptation (eye); Measure (data warehouse); Context (archaeology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02287058,0.0007684789,0.0007146782,0.00218771,0.001340087,0.001349547,0.001417825,0.0008938864,0.005514272],"category_scores_gemma":[0.02818018,0.0007798177,0.002024706,0.001351079,0.001070373,0.001148806,0.00250396,0.001960585,0.002301921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007896873,"about_ca_system_score_gemma":0.002752972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0017739,"about_ca_topic_score_gemma":0.002924451,"domain_scores_codex":[0.9940753,0.002269385,0.0008682181,0.0005795296,0.001925106,0.0002823717],"domain_scores_gemma":[0.9816048,0.008510731,0.001046542,0.002072548,0.006014141,0.0007512162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003617087,0.007252296,0.4652562,0.001624245,0.0006395906,0.0004378627,0.01544574,0.002688905,0.009853016,0.006205291,0.02395503,0.4630248],"study_design_scores_gemma":[0.001711542,0.007526588,0.8935761,0.001025626,0.0003259759,0.0008691404,0.006933546,0.00965357,0.004144373,0.006899553,0.06711303,0.0002208351],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8885018,0.001049113,0.04851486,0.000893224,0.0006166071,0.03253378,0.003658856,0.0006970747,0.02353473],"genre_scores_gemma":[0.7374247,0.001328985,0.1465032,0.0006563974,0.0002407398,0.09534568,0.007585095,0.0006298639,0.0102854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02287058,"threshold_uncertainty_score":0.1209527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049851188134217,"score_gpt":0.218817929142319,"score_spread":0.2083194172609768,"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."}}