{"id":"W322979443","doi":"10.1007/978-1-4939-0752-6_5","title":"Inclusion of A Priori Information Using Neural Networks","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Invenia (Canada)","funders":"","keywords":"A priori and a posteriori; Inclusion (mineral); Artificial neural network; Computer science; Artificial intelligence; Psychology; Epistemology; Social psychology; Philosophy","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":[0.0001130654,0.0001963811,0.0003034612,0.0002163832,0.0000580034,0.00002491684,0.0001235353,0.0001667149,0.0001292808],"category_scores_gemma":[0.000003719377,0.0001893283,0.0001346508,0.00002876363,0.00002263649,0.00008916105,0.0001770935,0.0002119357,0.00001467655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000545914,"about_ca_system_score_gemma":0.000005760999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003371586,"about_ca_topic_score_gemma":0.000004544112,"domain_scores_codex":[0.9992689,0.000004541942,0.0003770187,0.00007947833,0.0001440925,0.0001259153],"domain_scores_gemma":[0.9995475,0.00001632727,0.0001048645,0.0002437719,0.00004900089,0.00003849268],"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":[0.000003123302,0.00000105788,0.00001323529,0.0002478443,0.0001182348,9.611103e-7,0.0002208026,0.9471179,0.0005739006,0.001236169,0.001651761,0.04881498],"study_design_scores_gemma":[0.00006245454,0.000006057158,0.000003214316,0.0001118131,0.00007486275,0.000005881896,0.000001753047,0.9737453,0.00008982995,0.0001193919,0.02558851,0.0001909665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002381603,0.0004429364,0.626254,0.00002751455,0.0004720774,0.0001191558,0.000008707192,0.0003636685,0.3699303],"genre_scores_gemma":[0.9698991,0.0001281143,0.002385397,0.0001393015,0.0002673011,0.000001003991,0.0001200524,0.00007817306,0.02698159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9675174,"threshold_uncertainty_score":0.7720585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00768895911274019,"score_gpt":0.1903854889077718,"score_spread":0.1826965297950316,"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."}}