{"id":"W4295038044","doi":"10.1155/2022/2235542","title":"Application and Analysis of Improved Fuzzy Comprehensive Evaluation Method in Goodwill Evaluation and Intangible Asset Management","year":2022,"lang":"en","type":"article","venue":"Computational Intelligence and Neuroscience","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Goodwill; Intangible asset; Computer science; Fuzzy logic; Asset (computer security); Construct (python library); Convolutional neural network; Asset management; Feature (linguistics); Curse of dimensionality; Data mining; Artificial intelligence; Risk analysis (engineering); Business; Finance; Computer security","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":[0.002474229,0.0006656741,0.0005499308,0.002525555,0.0005319765,0.001473219,0.0005210795,0.0006265342,0.002378176],"category_scores_gemma":[0.005055476,0.0001628971,0.000716891,0.001540428,0.0006049068,0.002160606,0.0006594138,0.0005365959,0.0001556573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613405,"about_ca_system_score_gemma":0.001185545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0055915,"about_ca_topic_score_gemma":0.004442616,"domain_scores_codex":[0.9983707,0.0003642823,0.00009263538,0.0002426208,0.0008193304,0.0001104908],"domain_scores_gemma":[0.9984154,0.0005195365,0.0001364482,0.0001033889,0.0007504098,0.00007484269],"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":[0.0003917226,0.0002888076,0.01626086,0.0004140213,0.0002760061,0.0002764194,0.0009295425,0.2248254,0.0262608,0.07382264,0.003574393,0.6526794],"study_design_scores_gemma":[0.00002824972,0.0002271715,0.01205098,0.00004805756,0.00009288469,0.0001607836,0.0002845241,0.9533584,0.01268966,0.01801438,0.00295379,0.00009113157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1289655,0.0009629475,0.856091,0.0004103319,0.00008612203,0.0001467855,0.00009158877,0.0003423371,0.01290345],"genre_scores_gemma":[0.8684913,0.000386233,0.1285115,0.00004870168,0.00003036301,0.00008487327,0.00006877443,0.0000263566,0.002351963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0055915,"threshold_uncertainty_score":0.01308513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09813954082350825,"score_gpt":0.4005846653977563,"score_spread":0.3024451245742481,"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."}}