{"id":"W4407941909","doi":"10.1016/j.tsc.2025.101805","title":"Does ICT matter for complex problem-solving competency? A multilevel analysis of 33 countries and economies","year":2025,"lang":"en","type":"article","venue":"Thinking Skills and Creativity","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Shanghai Municipal Human Resources and Social Security Bureau; Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China; Shanghai Jiao Tong University; Universidade de Macau; Ministry of Education of the People's Republic of China","keywords":"Information and Communications Technology; Multilevel model; Economics; Business; Econometrics; Psychology; Computer science; Statistics; Mathematics","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":[0.002550822,0.0006686526,0.001473263,0.002908776,0.001564736,0.002943302,0.000912249,0.0006799696,0.002947481],"category_scores_gemma":[0.005661055,0.0006287571,0.003338522,0.005815963,0.001761741,0.001630837,0.004129226,0.001224861,0.000308987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041293,"about_ca_system_score_gemma":0.001893592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07600049,"about_ca_topic_score_gemma":0.06356728,"domain_scores_codex":[0.9972336,0.001256297,0.000163757,0.000403436,0.0002332872,0.0007096487],"domain_scores_gemma":[0.9910484,0.004627498,0.001999922,0.0007455622,0.0007975659,0.0007810765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001315713,0.00008517632,0.9936284,0.00003807428,0.00147165,0.000155693,0.0007981876,0.000803242,0.00008898192,0.0004757187,0.000164604,0.002158564],"study_design_scores_gemma":[0.00001643762,0.0001421792,0.9937614,0.00005237128,0.0005914996,0.00007013427,0.003539768,0.001133404,0.00008494992,0.000240525,0.0003496245,0.00001782083],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988741,0.0002054805,0.0001692724,0.00004545402,0.00000255487,0.000007152187,0.0002813403,0.00000350947,0.000411198],"genre_scores_gemma":[0.9993833,0.00006985894,0.0001040221,0.00001148914,0.000001798619,0.00001288513,0.0003162025,0.000002758632,0.00009775032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07600049,"threshold_uncertainty_score":0.1511162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236213147893896,"score_gpt":0.3064669278178448,"score_spread":0.2941047963389058,"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."}}