{"id":"W1596277605","doi":"10.1007/978-3-540-30227-8_36","title":"Two Approaches to Merging Knowledge Bases","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Belief revision; Merge (version control); Computer science; Knowledge base; Consistency (knowledge bases); Logical consequence; Operator (biology); Theoretical computer science; Algorithm; Artificial intelligence; Information retrieval","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010903,0.0008220485,0.000764753,0.001251218,0.000452773,0.0008296157,0.005220021,0.0002950495,0.00004092553],"category_scores_gemma":[0.0001691721,0.0007184881,0.0002343976,0.001217402,0.0006035617,0.0006611091,0.002905241,0.0008652752,0.0003860275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006845631,"about_ca_system_score_gemma":0.001313497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004470294,"about_ca_topic_score_gemma":0.0002701724,"domain_scores_codex":[0.9949547,0.00005267368,0.0005773972,0.002422889,0.0008624024,0.001129906],"domain_scores_gemma":[0.9967465,0.000500023,0.0002330734,0.001839857,0.00022168,0.00045888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000410871,0.00006978848,0.00004186567,0.00005337788,0.00001383028,0.0000868797,0.003093525,0.02911289,0.00004180089,0.3919993,0.00004387496,0.5754387],"study_design_scores_gemma":[0.001040942,0.0005247546,0.0001753673,0.001570632,0.00003056533,0.0002088308,0.000001241181,0.3594979,0.00457316,0.6151489,0.01436246,0.002865295],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005111401,0.001340203,0.9156576,0.0007407653,0.002413548,0.0004875741,0.000002967498,0.0003350631,0.0789711],"genre_scores_gemma":[0.4067596,0.00003189567,0.5883458,0.001540753,0.00148471,0.00003313525,0.000005474104,0.00007508455,0.001723596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5725735,"threshold_uncertainty_score":0.9995266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05988864282738988,"score_gpt":0.2605505624383962,"score_spread":0.2006619196110064,"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."}}