{"id":"W4401912148","doi":"10.54808/wmsci2024.01.210","title":"Navigating Digital Transformation: Crafting Tailored Data Strategies for Organizational Adaptability","year":2024,"lang":"en","type":"article","venue":"Proceedings","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Adaptability; Digital transformation; Computer science; Transformation (genetics); Knowledge management; Process management; Business; World Wide Web; Management","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":[0.02124947,0.001006102,0.0005839098,0.003592191,0.002014931,0.01283558,0.00219686,0.002230161,0.001846086],"category_scores_gemma":[0.03162099,0.0007279588,0.0007063127,0.001881471,0.005106672,0.01496874,0.009430867,0.002292414,0.0009449557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002728973,"about_ca_system_score_gemma":0.005423164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00147101,"about_ca_topic_score_gemma":0.001938236,"domain_scores_codex":[0.9847565,0.008797163,0.001358736,0.001354732,0.002520274,0.001212561],"domain_scores_gemma":[0.9781362,0.009560263,0.002341793,0.005423336,0.002709015,0.001829329],"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":[0.0001943815,0.0008562685,0.02517148,0.001309501,0.0001958593,0.0007507931,0.04621601,0.01777772,0.01854427,0.2268843,0.006271597,0.6558278],"study_design_scores_gemma":[0.0001929014,0.001577809,0.01130044,0.002010201,0.0002536085,0.001167687,0.09051231,0.08308201,0.03190834,0.5450595,0.2325859,0.0003492892],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1523494,0.0006415205,0.7871065,0.01002542,0.0001087122,0.001446765,0.0001059203,0.001529847,0.04668599],"genre_scores_gemma":[0.4730807,0.0003918856,0.5220017,0.0008902054,0.00002299021,0.0006917953,0.0001780141,0.0002717188,0.002470953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02124947,"threshold_uncertainty_score":0.1123793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09369779663219709,"score_gpt":0.3226558529170181,"score_spread":0.228958056284821,"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."}}