{"id":"W3190126589","doi":"10.4324/9781003020264-2","title":"Disrupting the alibi","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Alibi; Computer science; History; Archaeology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003526216,0.0004241652,0.0004559125,0.0002181901,0.0003720645,0.0006669021,0.0004561283,0.0001950825,0.01889221],"category_scores_gemma":[0.00010275,0.0002898014,0.0004621709,0.0001650845,0.00007981752,0.0004816407,0.0006121052,0.0003380415,0.002938002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003686563,"about_ca_system_score_gemma":0.00003097665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003689497,"about_ca_topic_score_gemma":0.0005866331,"domain_scores_codex":[0.9980702,0.000004821033,0.0005126357,0.0005338818,0.0005738282,0.0003046662],"domain_scores_gemma":[0.9984044,0.00006706716,0.0004603257,0.0007070026,0.0003512447,0.000009922433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005062924,0.000009858598,0.003497852,0.00009995568,0.00004215243,0.00005289376,0.00001260005,0.000004048705,0.00001088947,0.9554702,0.03818188,0.002612628],"study_design_scores_gemma":[0.00009859609,0.000001889543,0.0007516832,0.0001957426,0.0003774894,0.000001480719,0.00002735317,0.0005059383,0.000003242132,0.01103,0.9865795,0.0004271018],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006904641,0.0005816404,0.00002455346,0.0007895615,0.0005076947,0.000224801,0.000003093628,0.0001537593,0.9970244],"genre_scores_gemma":[0.01042145,0.00006910949,0.0001233326,0.005919188,0.004151591,0.00000828914,0.0003251411,0.0001073558,0.9788746],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9483976,"threshold_uncertainty_score":0.9999554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02126699597532708,"score_gpt":0.2145596136355535,"score_spread":0.1932926176602264,"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."}}