{"id":"W7154151203","doi":"10.1145/3772318.3809054","title":"10.1145/3772318.3809054","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Personalization; Component (thermodynamics); Key (lock)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001853091,0.003937767,0.00268043,0.003196557,0.00272054,0.005148042,0.003397812,0.005526376,0.9404293],"category_scores_gemma":[0.003406989,0.002021252,0.001421189,0.01122895,0.001573431,0.01200724,0.006127434,0.003019753,0.9605417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002730333,"about_ca_system_score_gemma":0.001272047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02215018,"about_ca_topic_score_gemma":0.01744153,"domain_scores_codex":[0.9991411,0.00006142334,0.00007526003,0.0002644014,0.0002925873,0.0001650752],"domain_scores_gemma":[0.9985583,0.0003361592,0.00007118523,0.0004906121,0.0003186564,0.0002250084],"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":[0.0002550631,0.0001700099,0.0004868724,0.0007858262,0.00005390154,0.000252675,0.0001138204,0.0007735486,0.001337969,0.007454243,0.6592943,0.3290218],"study_design_scores_gemma":[0.00003611161,0.00003121062,0.0007720785,0.0002953992,0.00005124488,0.0001547878,0.00008189235,0.0008619119,0.000485951,0.001750953,0.9954376,0.00004098402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00263348,0.008747759,0.01423284,0.00146955,0.002337415,0.0005328882,0.02037027,0.01828925,0.9313865],"genre_scores_gemma":[0.004265079,0.003293358,0.002531605,0.0007457547,0.0001436205,0.0002594005,0.01126391,0.00220933,0.975288],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05957067,"threshold_uncertainty_score":0.08497024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102177920855491,"score_gpt":0.1979375609914797,"score_spread":0.1877197689059306,"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."}}