{"id":"W2995831954","doi":"10.32370/ia_2019_12_17","title":"PATENT PROTECTION OF INTEGRATIVE TECHNICAL SYSTEM – containing subsystems interconnected by elements of artificial intelligence and artificial neural networks. The use of analytical and algorithmic tools in the preparation of applications for the issuance of patent documents in the United States","year":2019,"lang":"en","type":"article","venue":"Intellectual Archive","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Computer science; Systems engineering; Hierarchy; Product (mathematics); Manufacturing engineering; Artificial intelligence; Management science; Risk analysis (engineering); Engineering management; Engineering; Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008690926,0.0001135221,0.0002738152,0.000136513,0.0000254837,0.00001160775,0.0002343026,0.00006303658,7.320683e-7],"category_scores_gemma":[0.0006143922,0.00005730948,0.0000403562,0.0003984505,0.0002859739,0.00005195746,0.00004723688,0.0002483313,5.271287e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001952129,"about_ca_system_score_gemma":0.000007628867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002464748,"about_ca_topic_score_gemma":0.0001241104,"domain_scores_codex":[0.9986945,0.0002875356,0.0006708548,0.000122754,0.0001056207,0.0001187558],"domain_scores_gemma":[0.9952796,0.004249557,0.0001842881,0.0001983252,0.00008114022,0.000007152266],"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":[0.002244611,0.0002844316,0.00148544,0.000975203,0.0004059562,6.29308e-7,0.05171046,0.7854671,0.06119597,0.02946766,0.00005213145,0.06671035],"study_design_scores_gemma":[0.00009087096,0.0005466226,0.0004921237,0.0001934922,0.00003198015,0.000003930863,0.01274045,0.9641167,0.02092675,0.0007840608,0.00002032045,0.00005270606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5493851,0.00008327412,0.4490325,0.00002853158,0.00002534854,0.001399901,0.00003290445,0.00001065703,0.000001822971],"genre_scores_gemma":[0.9986108,0.00008010609,0.0009016927,0.000003283291,0.000006160721,0.0003710827,0.00001995757,0.000006401743,5.207162e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4492257,"threshold_uncertainty_score":0.2337013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1469090516662193,"score_gpt":0.3164564294788328,"score_spread":0.1695473778126136,"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."}}