{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002354625,0.0004630315,0.0004707315,0.001816334,0.00035271,0.002528605,0.0006400623,0.001480575,0.005991298],"category_scores_gemma":[0.02296292,0.0002084603,0.000317589,0.001910901,0.0007437996,0.005211491,0.0007113961,0.001503918,0.001036258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001361747,"about_ca_system_score_gemma":0.0006038391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00328157,"about_ca_topic_score_gemma":0.003012829,"domain_scores_codex":[0.999411,0.0002335597,0.00004490423,0.00008852658,0.0001325161,0.0000895007],"domain_scores_gemma":[0.984149,0.01205708,0.002019651,0.000564087,0.0007232878,0.0004868112],"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":[0.002836868,0.002304213,0.1068884,0.0004802256,0.0003507647,0.0005816586,0.0003200564,0.1655177,0.006510568,0.07557886,0.03885359,0.5997772],"study_design_scores_gemma":[0.00009333986,0.0001849192,0.03043544,0.00009175606,0.00006265842,0.0001172667,0.0001110104,0.7764886,0.001985275,0.1863113,0.004079159,0.00003922904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9175888,0.007640701,0.04148684,0.01092539,0.0004791786,0.00004100147,0.003309927,0.0006027208,0.01792539],"genre_scores_gemma":[0.9912527,0.000730183,0.00254398,0.0001351413,0.0002562604,0.0000101404,0.000929966,0.00002401816,0.004117467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005991298,"threshold_uncertainty_score":0.02004296,"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."}}