{"id":"W98619017","doi":"","title":"Target: The Challenge of Data Mining","year":2013,"lang":"en","type":"article","venue":"Journal of critical incidents","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Purchasing; Clothing; Marketing; Value (mathematics); Product (mathematics); Business; Earnings; Portfolio; Target market; Advertising; Quarter (Canadian coin); Computer science; Finance","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":[],"category_scores_codex":[0.000556064,0.00006766908,0.0001523342,0.0001064743,0.00007473657,0.0001436872,0.000548595,0.00002980671,0.0009688655],"category_scores_gemma":[0.0006466986,0.00004317229,0.00005183438,0.0001225736,0.00008280292,0.002588621,0.0002202105,0.0001292874,0.0001092534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000112584,"about_ca_system_score_gemma":0.00001122451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217469,"about_ca_topic_score_gemma":0.00001261141,"domain_scores_codex":[0.9989163,0.00001405038,0.0004367359,0.00007871592,0.0004223419,0.000131877],"domain_scores_gemma":[0.9990155,0.0001365204,0.0002416657,0.0002047612,0.0003858802,0.00001571512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000449082,0.004638123,0.1691271,0.003125558,0.0008398918,0.0004141894,0.005309997,0.00009956298,0.015305,0.08962619,0.3668126,0.3442527],"study_design_scores_gemma":[0.008795672,0.0004949215,0.5211323,0.001993967,0.001785601,0.0002370855,0.03913205,0.0558537,0.001531044,0.2456742,0.1215972,0.001772289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574311,0.0006761294,0.002090575,0.02253692,0.001184013,0.0001810701,0.000003605822,0.00001348854,0.01588312],"genre_scores_gemma":[0.9972121,0.00001168532,0.0008184605,0.0009649094,0.0009517542,0.000001011809,0.000003781162,0.000008317425,0.00002804979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3520051,"threshold_uncertainty_score":0.9999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08359983349132527,"score_gpt":0.3345085585989577,"score_spread":0.2509087251076324,"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."}}