{"id":"W6894167100","doi":"10.5281/zenodo.8201929","title":"CREDIT CARDS CANADA","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Credit card; Payment; Government (linguistics); Credit card interest; Debt","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002172887,0.00007984104,0.0001068849,0.00010272,0.0008645324,0.0001378024,0.000267039,0.00002356094,0.0115489],"category_scores_gemma":[0.0002036338,0.00007820458,0.00003694536,0.0005173059,0.00004216181,0.0000691879,0.0005080316,0.0001710477,0.00391089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002311209,"about_ca_system_score_gemma":0.0000160037,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01828555,"about_ca_topic_score_gemma":0.0002609658,"domain_scores_codex":[0.9989353,0.0000684955,0.0001285158,0.0002074989,0.0003879413,0.0002722868],"domain_scores_gemma":[0.9992481,0.00001272383,0.00002777173,0.0003023618,0.0002100047,0.0001990649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004943617,0.0000269268,0.00001853405,0.00003874347,0.00003172517,0.0001989195,0.0001423057,0.00001042313,0.00169725,0.0003853244,0.9728144,0.02458603],"study_design_scores_gemma":[0.000458598,0.0001434408,0.003645322,0.00001777078,0.00001799549,0.0002017454,0.0002715008,0.0001825745,0.0003169922,0.00001684093,0.9946453,0.00008192178],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5445902,0.0001930576,0.0002141069,0.02757703,0.0006440225,0.0008566427,0.0007744987,0.00254122,0.4226093],"genre_scores_gemma":[0.9907029,0.00005715167,0.00003476741,0.00130627,0.0003442776,2.407178e-8,0.003027407,0.0008478225,0.003679325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4461128,"threshold_uncertainty_score":0.9968647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03336723609077415,"score_gpt":0.2530751109170676,"score_spread":0.2197078748262935,"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."}}