{"id":"W1538134818","doi":"10.13140/2.1.1779.4243","title":"Neural-Symbolic Learning and Reasoning: Contributions and Challenges","year":2015,"lang":"en","type":"article","venue":"City Research Online (City University London)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Connectionism; Computer science; Artificial intelligence; Artificial neural network; Representation (politics); Computation; Knowledge representation and reasoning; Symbolic-numeric computation; Key (lock); Models of neural computation; The Symbolic; Cognitive science; Machine learning; Programming language; Psychology","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":[0.001461976,0.0001453559,0.000221808,0.0003542543,0.0005971419,0.0002023199,0.0007404006,0.0001506907,0.00000259125],"category_scores_gemma":[0.001705278,0.0001499369,0.00003247796,0.0006416211,0.0004360797,0.0009412966,0.001742828,0.001114039,0.00000217081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001805914,"about_ca_system_score_gemma":0.0001962213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004177045,"about_ca_topic_score_gemma":0.0003059252,"domain_scores_codex":[0.9978234,0.0005345797,0.0001039812,0.0005331463,0.0005139113,0.0004909616],"domain_scores_gemma":[0.9980295,0.0002981485,0.00005715345,0.0003129348,0.0008208044,0.0004814664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003506691,0.0007668849,0.03891345,0.0003148217,0.0001297119,0.001123634,0.007064649,0.00001324095,0.00192802,0.6760266,0.002567308,0.270801],"study_design_scores_gemma":[0.009722778,0.003314971,0.04684414,0.0007944966,0.0001008831,0.001014928,0.007860241,0.2068559,0.005939709,0.1239601,0.5906746,0.002917145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8920778,0.03251297,0.03183172,0.03951618,0.00009811672,0.0006214857,0.00007567841,0.001539047,0.001726973],"genre_scores_gemma":[0.9389432,0.004862523,0.05488673,0.00005499733,0.00008257803,9.789718e-7,0.00002317759,0.00001012765,0.001135656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5881073,"threshold_uncertainty_score":0.6114249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09420937839203838,"score_gpt":0.3544807468344663,"score_spread":0.2602713684424279,"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."}}