{"id":"W2913161133","doi":"10.3166/isi.23.5.185-200","title":"Design and application of a wavelet neural network program for evaluation of goodwill value in corporate intellectual capital","year":2018,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Intellectual Capital and Performance Analysis","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Goodwill; Intellectual capital; Wavelet; Value (mathematics); Business; Accounting; Finance; Computer science; Artificial intelligence; Machine learning","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":[0.0009459421,0.0003365642,0.0002525308,0.0005282749,0.0002702791,0.0004826767,0.0007790304,0.0004846615,0.002813037],"category_scores_gemma":[0.002446193,0.0002375184,0.0001980833,0.000345472,0.0002343158,0.0004464722,0.0003262211,0.0003597732,0.0002705983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004843901,"about_ca_system_score_gemma":0.0008417463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003885687,"about_ca_topic_score_gemma":0.002779234,"domain_scores_codex":[0.9997417,0.00008455132,0.00001360065,0.00006139992,0.00007378926,0.00002499599],"domain_scores_gemma":[0.9991207,0.0004503067,0.0000610739,0.00004145742,0.0002851867,0.00004134891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000975985,0.0006549924,0.007739779,0.0001810427,0.00009841,0.00014758,0.0001683401,0.4904766,0.06176981,0.005462733,0.0009489045,0.4313759],"study_design_scores_gemma":[0.00002198229,0.00009765106,0.0005120518,0.000002315357,0.00001101765,0.000007987041,0.000008191293,0.9912286,0.007629474,0.0002816523,0.0001953011,0.000003712669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1451384,0.00002761923,0.8506179,0.0000764064,0.00002642545,0.0004396782,0.00007035196,0.001146658,0.002456609],"genre_scores_gemma":[0.6642023,0.00003469273,0.3329423,0.00003733654,0.00001063122,0.0005998315,0.0001021582,0.0001045742,0.001966156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003885687,"threshold_uncertainty_score":0.00941056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03055196288563813,"score_gpt":0.248869185558139,"score_spread":0.2183172226725009,"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."}}