{"id":"W1588404442","doi":"10.1007/978-3-540-73580-9_27","title":"An Analysis of Map-Based Abstraction and Refinement","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Testbed; Abstraction; Variety (cybernetics); Computer science; Pathfinding; Theoretical computer science; Programming language; Artificial intelligence; World Wide Web; Graph","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":[0.001101265,0.0002814213,0.0004099698,0.002172039,0.0001019762,0.000327821,0.001702798,0.0001333646,0.00002555111],"category_scores_gemma":[0.00001226262,0.0002597543,0.00009153442,0.0009546813,0.000330591,0.000660317,0.0004570748,0.000262461,0.000004592479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010021,"about_ca_system_score_gemma":0.00009839902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006325617,"about_ca_topic_score_gemma":0.000186589,"domain_scores_codex":[0.9973977,0.00001473888,0.0004272609,0.001045698,0.0007925283,0.0003221005],"domain_scores_gemma":[0.998086,0.0001538917,0.0003034183,0.001211287,0.0001350449,0.0001103219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004828846,0.00005041839,0.0002021141,0.0000370159,0.00006289068,0.0000338239,0.0001362163,0.05471132,0.00009232576,0.01009538,0.00000773581,0.9345659],"study_design_scores_gemma":[0.0001559352,0.0001630571,0.002654196,0.00007073104,0.00009032981,0.000001423512,1.651802e-7,0.9886259,0.0006463379,0.005806716,0.001460726,0.0003245141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001860825,0.0001013289,0.9977908,0.0002234677,0.0005068446,0.0001573626,0.00001087792,0.00006087604,0.0009624354],"genre_scores_gemma":[0.1516882,0.00002887554,0.8469212,0.0009352558,0.0001731611,0.00000315324,0.00006832043,0.00001718397,0.000164689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9342414,"threshold_uncertainty_score":0.9999855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02182059924059719,"score_gpt":0.2736472474865811,"score_spread":0.2518266482459839,"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."}}