{"id":"W2123225485","doi":"10.1007/978-3-540-73208-2_4","title":"Information Distance and Applications","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Measure (data warehouse); Distance measures; Computer science; Artificial intelligence; Data mining","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":[0.001063615,0.000443998,0.0004019949,0.0007933228,0.0002972101,0.0007504405,0.002504766,0.0002787943,0.000008762612],"category_scores_gemma":[0.00006372834,0.0004252273,0.00007671168,0.0007950102,0.000857989,0.001433231,0.001651005,0.0006614879,0.00005349645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003353861,"about_ca_system_score_gemma":0.0003139439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001661027,"about_ca_topic_score_gemma":0.00006376875,"domain_scores_codex":[0.9969293,0.00001869105,0.0006174345,0.0009577753,0.0009045422,0.0005722653],"domain_scores_gemma":[0.9971978,0.0005036334,0.0003004987,0.001456543,0.0003327767,0.0002087627],"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":[0.000001535563,0.00001236151,0.00004631092,0.00003483419,0.000002949897,0.000006300666,0.0003415531,0.004547281,0.00000245428,0.09005973,0.000005694671,0.904939],"study_design_scores_gemma":[0.0002296904,0.0001051453,0.0005230219,0.0001143229,0.000005772556,0.00009440725,3.190596e-7,0.5339752,0.000113455,0.4304321,0.033655,0.0007516007],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000009393008,0.0004576513,0.9904407,0.0004184558,0.0007100321,0.0006901062,0.000007534575,0.0002379652,0.007028157],"genre_scores_gemma":[0.03865285,0.00008672608,0.9581732,0.002193077,0.0006515987,0.00004132735,0.0000147111,0.00002620862,0.0001603584],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9041874,"threshold_uncertainty_score":0.9998199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441703269694057,"score_gpt":0.2465952413060176,"score_spread":0.232178208609077,"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."}}