{"id":"W3127947948","doi":"10.2139/ssrn.3758388","title":"Deep Learning, Text, and Patent Valuation","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Deep learning; Artificial intelligence; Valuation (finance); Computer science; Value (mathematics); Machine learning; Econometrics; Natural language processing; Actuarial science; Economics; Accounting","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006930424,0.000112481,0.0001078044,0.00006925289,0.0003168061,0.0001994139,0.0001228153,0.00004387823,0.0002419219],"category_scores_gemma":[0.0002940149,0.00008830591,0.00004999022,0.0001691501,0.00002105678,0.000504551,0.00005840463,0.001046145,0.0004991757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007738757,"about_ca_system_score_gemma":0.00009040259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009453328,"about_ca_topic_score_gemma":0.00009582346,"domain_scores_codex":[0.9986138,0.00002360389,0.0001715014,0.0001507954,0.0002024966,0.0008377754],"domain_scores_gemma":[0.9996988,0.0000175961,0.0001246267,0.00003803613,0.0001026304,0.00001829505],"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":[0.0005530226,0.0001433905,0.04677611,0.0001503948,0.0004031323,0.00002165456,0.001609277,0.00329687,0.002152785,0.2144656,0.001373258,0.7290545],"study_design_scores_gemma":[0.003830052,0.000905188,0.004191461,0.00008354386,0.0003457255,0.0001841191,0.00834393,0.47385,0.0001329209,0.3001969,0.2068465,0.001089668],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8938168,0.006113361,0.06919613,0.01119518,0.0004965686,0.0003932772,1.991259e-7,0.0002108348,0.01857762],"genre_scores_gemma":[0.9954397,0.0008745499,0.00001300996,0.001891072,0.001091878,0.00000192084,0.000005047233,0.00001858325,0.0006642516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7279648,"threshold_uncertainty_score":0.641606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0907647716789483,"score_gpt":0.2170407829074088,"score_spread":0.1262760112284605,"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."}}