{"id":"W2117624436","doi":"","title":"Bike: Bilingual Keyphrase Experiments","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Machine translation; Information retrieval; Resource (disambiguation)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003826686,0.001345101,0.001072336,0.001048746,0.001774793,0.001208491,0.001507406,0.002080942,0.01926045],"category_scores_gemma":[0.01555805,0.000457377,0.0006046298,0.001338159,0.0006414304,0.00290982,0.00196856,0.002019439,0.007536045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006018698,"about_ca_system_score_gemma":0.0009169517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003062127,"about_ca_topic_score_gemma":0.003105475,"domain_scores_codex":[0.9969824,0.00161199,0.0002785821,0.0005308376,0.0004079661,0.0001881263],"domain_scores_gemma":[0.9886193,0.007632175,0.000296673,0.00178714,0.001253053,0.0004116922],"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":[0.03792142,0.01639307,0.01023898,0.007779283,0.001219912,0.002458859,0.004879339,0.03680809,0.1500615,0.02546483,0.1997358,0.507039],"study_design_scores_gemma":[0.01228632,0.01935126,0.02690351,0.0004999197,0.0007888356,0.003823682,0.004925739,0.3727874,0.2466315,0.04674223,0.2645427,0.0007169448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8037132,0.002696411,0.08260033,0.001653294,0.001414712,0.002340543,0.02332486,0.02163437,0.0606222],"genre_scores_gemma":[0.8214262,0.0005204938,0.1187787,0.0009174426,0.0001769022,0.002210739,0.03209884,0.002331928,0.02153875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01926045,"threshold_uncertainty_score":0.06443268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699604029499381,"score_gpt":0.3099215250640071,"score_spread":0.2929254847690133,"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."}}