{"id":"W4413327133","doi":"10.1007/978-981-96-7269-1_17","title":"Measuring Digital Economy Progress in Liaoning Province: An Empirical Study Using Factor Analysis","year":2025,"lang":"en","type":"book-chapter","venue":"Smart innovation, systems and technologies","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Factor (programming language); Digital economy; Economy; Economics; Business; Computer science; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001369206,0.0004789494,0.001144537,0.007657462,0.0002871809,0.001150098,0.000938372,0.001012831,0.00001393615],"category_scores_gemma":[0.0005073484,0.0003929262,0.0001088399,0.002836134,0.000390188,0.0008308173,0.0006051467,0.0007894626,0.000008132508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002163217,"about_ca_system_score_gemma":0.0002703411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003268651,"about_ca_topic_score_gemma":0.0002056918,"domain_scores_codex":[0.9958332,0.00005087777,0.00189432,0.00123664,0.0006513865,0.0003335745],"domain_scores_gemma":[0.9966578,0.0001478538,0.0009989521,0.001213374,0.0009523552,0.0000296994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008620194,0.00008596582,0.9486219,0.00002159923,0.0002001187,0.00002620224,0.0001283998,0.00001316545,0.000001127758,0.02981292,0.00008249323,0.02099748],"study_design_scores_gemma":[0.002473765,0.001002677,0.7885576,0.001114701,0.0009041422,0.00008157851,0.04479477,0.006516179,0.00005644314,0.07844262,0.07245282,0.003602662],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870294,0.000994712,0.00148118,0.0003878465,0.0003395549,0.001567216,0.0001071743,0.001294858,0.006798096],"genre_scores_gemma":[0.9857517,0.000006725381,0.0002429096,0.00001172375,0.00002547705,0.00007200788,0.00002812216,0.00002485984,0.01383645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1600643,"threshold_uncertainty_score":0.9998868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1957934560129699,"score_gpt":0.3875164371217889,"score_spread":0.191722981108819,"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."}}