{"id":"W7154168698","doi":"10.1145/3772318.3808976","title":"10.1145/3772318.3808976","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); Component (thermodynamics); Key (lock); Training (meteorology)","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":[0.001818682,0.003938006,0.002548029,0.003234759,0.002663599,0.005049164,0.003233314,0.005233611,0.9424516],"category_scores_gemma":[0.003321498,0.001996894,0.001401829,0.01077309,0.001535233,0.0116055,0.006030623,0.002874961,0.9617615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002702496,"about_ca_system_score_gemma":0.001289512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02135649,"about_ca_topic_score_gemma":0.01772078,"domain_scores_codex":[0.9991498,0.00006004255,0.000076233,0.000261206,0.0002871034,0.0001656927],"domain_scores_gemma":[0.9985653,0.0003267581,0.00007141325,0.0004865882,0.0003206217,0.0002294139],"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":[0.0002467789,0.0001621356,0.0004775512,0.0007384104,0.00005079007,0.0002398261,0.0001075889,0.0007336908,0.001311744,0.007182426,0.6626702,0.3260789],"study_design_scores_gemma":[0.0000360187,0.0000309437,0.0007745228,0.0002841278,0.00004836089,0.0001491994,0.00008013169,0.000834355,0.000489435,0.001733073,0.9954992,0.00004061744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002388486,0.007938439,0.01391304,0.001383687,0.002266782,0.0005135643,0.01924078,0.01766285,0.9346924],"genre_scores_gemma":[0.003941794,0.003110494,0.002447352,0.0007364617,0.0001330872,0.0002503289,0.01114995,0.002146833,0.9760838],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0575484,"threshold_uncertainty_score":0.08208573,"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."}}