{"id":"W2163490678","doi":"","title":"Use of Keyphrase Extraction Software for Creation of an AEC/FM Thesaurus","year":2000,"lang":"en","type":"article","venue":"NPARC","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thesaurus; Extractor; Computer science; Software; The Internet; Process (computing); Domain (mathematical analysis); Information retrieval; World Wide Web; Software engineering; Natural language processing; Engineering","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":[0.003619203,0.001673528,0.001294878,0.01162616,0.001719408,0.002654992,0.0009423865,0.0009737891,0.01154616],"category_scores_gemma":[0.01391208,0.001121024,0.001536525,0.007549906,0.0008100573,0.002939845,0.001683973,0.001745355,0.007860834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009826481,"about_ca_system_score_gemma":0.002101892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00310612,"about_ca_topic_score_gemma":0.003259528,"domain_scores_codex":[0.998265,0.0003273671,0.0004480761,0.0004450889,0.0004536922,0.00006097325],"domain_scores_gemma":[0.9935941,0.003272327,0.000437583,0.0008081479,0.00175833,0.0001295159],"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":[0.0002446287,0.0001099319,0.001538824,0.001948245,0.0001656801,0.0009047514,0.003210379,0.001711564,0.06611757,0.01072498,0.01187109,0.9014524],"study_design_scores_gemma":[0.0004110356,0.0006805463,0.01159548,0.0008131212,0.0006748285,0.006310679,0.002773682,0.1236002,0.3001527,0.02951874,0.5229172,0.0005517448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008685693,0.000220022,0.9615673,0.0001178506,0.0000890117,0.001044079,0.002056347,0.0221804,0.004039361],"genre_scores_gemma":[0.0129864,0.0001380504,0.980975,0.00003140825,0.00001766748,0.0005722399,0.002145686,0.0014901,0.001643442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01162616,"threshold_uncertainty_score":0.03862578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02853358991606894,"score_gpt":0.3131675310217468,"score_spread":0.2846339411056779,"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."}}