{"id":"W6894350823","doi":"10.5683/sp3/s1b5nh","title":"Replication Data and Code for: Tax Compliance and Firm Response to Electronic Sales Monitoring","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Replication (statistics); Compliance (psychology); Code (set theory); Replicate; Data file; Line (geometry)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003524905,0.002072569,0.00152594,0.004409937,0.001406333,0.00337598,0.003553458,0.002240385,0.176819],"category_scores_gemma":[0.02585264,0.001319829,0.00188874,0.008869187,0.0006935162,0.001743688,0.00228541,0.002622528,0.154538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002633645,"about_ca_system_score_gemma":0.004469706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07109419,"about_ca_topic_score_gemma":0.1014214,"domain_scores_codex":[0.9963459,0.0007080836,0.0005009258,0.001046656,0.0009384797,0.0004600281],"domain_scores_gemma":[0.9849103,0.003673569,0.001634989,0.00464831,0.004353532,0.0007793056],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005395249,0.00001738605,0.0009256673,0.0001737764,0.00002186244,0.000008372002,0.00001901649,0.0001434779,0.00003223076,0.0003367915,0.9972831,0.0009843966],"study_design_scores_gemma":[0.0007194303,0.00003292035,0.01247431,0.0003001029,0.00006999725,0.0000634246,0.0001485437,0.0005602937,0.0004254061,0.00214698,0.9829797,0.00007890301],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001250948,0.00001394038,0.00008079475,0.0000638178,0.00002846989,0.00002080426,0.9986684,0.0002904535,0.0007081369],"genre_scores_gemma":[0.0007646277,0.00001629673,0.0003977931,0.00006858711,0.00001286549,0.0002325143,0.9965892,0.0002401414,0.001677995],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9964751,"threshold_uncertainty_score":0.5915186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1177931720871576,"score_gpt":0.3885193555721073,"score_spread":0.2707261834849497,"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."}}