{"id":"W2767967947","doi":"10.1613/jair.5521","title":"Trust as a Precursor to Belief Revision","year":2018,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Access Control and Trust","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Belief revision; Class (philosophy); Partition (number theory); Computer science; Set (abstract data type); Representation (politics); Domain (mathematical analysis); Artificial intelligence; Mathematics; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.009057319,0.00009822613,0.0002457676,0.0005499901,0.001049881,0.0004083306,0.001001313,0.0001213984,0.002345968],"category_scores_gemma":[0.007088247,0.00007902204,0.0001291118,0.001478281,0.0007889339,0.0004846994,0.0001366451,0.0005802442,0.002882592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001957787,"about_ca_system_score_gemma":0.0008010633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001034471,"about_ca_topic_score_gemma":0.001066371,"domain_scores_codex":[0.9958678,0.0006570139,0.0006473613,0.000212895,0.001935332,0.0006795384],"domain_scores_gemma":[0.995422,0.0005727496,0.0001791572,0.0002115831,0.003068645,0.0005458322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006395269,0.0002141,0.0002722841,0.000007918791,0.0000274211,0.00005331137,0.01639338,0.00001413481,0.002086839,0.1090972,0.005921639,0.8652723],"study_design_scores_gemma":[0.00009742171,0.00437075,0.0003828883,0.0004189809,0.00002680554,0.00002574166,0.03480541,0.0004249912,0.04333319,0.1709313,0.7448279,0.0003545746],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7683447,0.000916871,0.02318992,0.0463662,0.002626508,0.001239638,0.000005491725,0.00005474749,0.1572559],"genre_scores_gemma":[0.9925605,0.0003253203,0.0009840628,0.000188538,0.004069156,0.000003821424,1.474239e-7,0.00001229879,0.001856168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8649177,"threshold_uncertainty_score":0.998566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2044539372773362,"score_gpt":0.518133020768067,"score_spread":0.3136790834907308,"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."}}