{"id":"W2351893935","doi":"","title":"Automatic Evaluation of Chinese Summarizations Based on Hybrid Strategy","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Computer science; Key (lock); Point (geometry); Artificial intelligence; Foundation (evidence); Natural language processing; Base (topology); Computer security; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003148003,0.001185695,0.0008973697,0.003876138,0.0005502011,0.00186093,0.0006473927,0.0004742517,0.002343729],"category_scores_gemma":[0.01048079,0.0001840183,0.0005003735,0.002626217,0.0003381167,0.002137559,0.000639529,0.0002861772,0.0006424819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008186502,"about_ca_system_score_gemma":0.0007697582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002111453,"about_ca_topic_score_gemma":0.00213959,"domain_scores_codex":[0.995583,0.001933125,0.0005922214,0.0006303797,0.001098949,0.0001622504],"domain_scores_gemma":[0.9928713,0.002291025,0.0005046945,0.0004342113,0.003692379,0.0002064547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001718264,0.0002511478,0.00819078,0.001149914,0.0004007942,0.0003615122,0.001653808,0.01193035,0.08664891,0.008676149,0.008564427,0.870454],"study_design_scores_gemma":[0.0006342955,0.003111076,0.04770218,0.0001577601,0.001346746,0.0008924346,0.003169639,0.7269576,0.1832341,0.01050663,0.02197575,0.0003119075],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4793175,0.002709222,0.4946381,0.0004532835,0.0002134642,0.001417108,0.001819233,0.006510649,0.01292147],"genre_scores_gemma":[0.7520363,0.000488129,0.2408887,0.00006576187,0.00008944594,0.000449776,0.002618967,0.0002068173,0.003156117],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003876138,"threshold_uncertainty_score":0.01664841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315909752254468,"score_gpt":0.3441529698475553,"score_spread":0.3209938723250106,"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."}}