{"id":"W2415075203","doi":"","title":"Distributed Multimedia Information Retrieval: Sigir 2003 Workshop on Distributed Information Retrieval, Toronto, Canada, August 2003: Revised, Selected, and Invited Papers (Lecture Notes in Computer Science, 2924)","year":2004,"lang":"en","type":"book","venue":"Springer eBooks","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Information retrieval; Multimedia information retrieval; Library science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008816542,0.0008643792,0.0007871152,0.0006554659,0.0004447712,0.001110596,0.001423977,0.0007938497,0.00002955786],"category_scores_gemma":[0.001851524,0.0008347377,0.00008337754,0.002520765,0.0004701888,0.002409381,0.000486561,0.001250489,0.00001665597],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007102661,"about_ca_system_score_gemma":0.009333451,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006628231,"about_ca_topic_score_gemma":0.008566436,"domain_scores_codex":[0.9948661,0.0001090678,0.001418871,0.0008585129,0.001759675,0.0009878213],"domain_scores_gemma":[0.9945224,0.0002109742,0.001022228,0.001195977,0.002591562,0.0004568392],"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":[0.001592786,0.0003509899,0.0003421946,0.002326597,0.0004245907,0.0001477255,0.00569671,0.001519825,0.001878592,0.009891978,0.07768655,0.8981414],"study_design_scores_gemma":[0.005642614,0.0008143257,0.01050179,0.004770178,0.0001843563,0.00008747748,0.00005537962,0.07908225,0.03500632,0.001296399,0.857224,0.005334872],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003231547,0.0006751327,0.975845,0.0008685159,0.001558414,0.004026644,0.001055314,0.001237103,0.01441072],"genre_scores_gemma":[0.4351595,0.00881396,0.3431737,0.06258772,0.005419762,0.001383722,0.07902654,0.001570744,0.06286436],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8928066,"threshold_uncertainty_score":0.9999867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007162143061243406,"score_gpt":0.2111470226439621,"score_spread":0.2039848795827187,"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."}}