{"id":"W2953258354","doi":"10.31142/ijtsrd18909","title":"Artificial Intelligence: Basics and Terminology","year":2018,"lang":"en","type":"article","venue":"International Journal of Trend in Scientific Research and Development","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Terminology; Computer science; Artificial intelligence; Linguistics; 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":[0.002579337,0.00007544759,0.0001101961,0.001076273,0.0002440895,0.0006263802,0.001067254,0.00004481838,0.00004111511],"category_scores_gemma":[0.0002359041,0.00006416896,0.00001590781,0.0005518247,0.0008854349,0.0005017675,0.0004941864,0.0002318348,0.00005143606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009939449,"about_ca_system_score_gemma":0.0003528591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006775228,"about_ca_topic_score_gemma":0.0003094616,"domain_scores_codex":[0.997921,0.00006972886,0.0005857866,0.0002985216,0.0008486898,0.000276299],"domain_scores_gemma":[0.9983742,0.0002102787,0.0001245405,0.0001749294,0.0009745507,0.0001415081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003282077,0.0001672419,0.00239705,0.000002379169,0.0000216481,0.00004955094,0.005217109,0.000004213088,0.001987791,0.09762255,0.0007842941,0.8917133],"study_design_scores_gemma":[0.000218626,0.000684674,0.02308808,0.0001727598,0.000002674789,0.0006630252,0.003042806,0.008681247,0.2401685,0.5093437,0.2135046,0.0004292798],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7162976,0.0002566066,0.2722199,0.007507414,0.002133603,0.0001659186,0.000002990392,0.00001667651,0.001399279],"genre_scores_gemma":[0.9584748,0.00004495884,0.04110855,0.00003902226,0.0001508971,0.000006192071,0.00000134154,0.000003121304,0.0001711226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.891284,"threshold_uncertainty_score":0.6040199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2180112288741696,"score_gpt":0.4478336660058447,"score_spread":0.2298224371316751,"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."}}