{"id":"W3017201749","doi":"10.1101/2020.04.20.051342","title":"Dendrites decrease the synaptic weight resolution necessary to implement linearly separable computations","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Computation; Soma; Perceptron; Neuromorphic engineering; Computer science; Constraint (computer-aided design); Models of neural computation; Artificial neural network; Complement (music); Synaptic weight; Algorithm; Artificial intelligence; Mathematics; Neuroscience","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003121889,0.000528331,0.0004451057,0.0001639655,0.0003798786,0.0002156541,0.0006216114,0.0002063256,0.00003351791],"category_scores_gemma":[0.0002382814,0.0005050364,0.0001431985,0.0006573048,0.00004174937,0.0001648656,0.0005361348,0.0009471255,0.0001290258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002585182,"about_ca_system_score_gemma":0.0001931237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001716802,"about_ca_topic_score_gemma":0.000003561451,"domain_scores_codex":[0.9976749,0.0001199721,0.0005703255,0.0007031497,0.0003172368,0.0006144537],"domain_scores_gemma":[0.9981267,0.0002192155,0.0001464035,0.0008107857,0.0002044901,0.0004923985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000046386,0.00007155783,0.0005023164,0.0007778099,0.0004086047,0.0001542946,0.0000753096,0.4445978,0.5480602,0.001267043,0.004023737,0.00001493491],"study_design_scores_gemma":[0.0010318,0.0002024557,0.02389368,0.001368236,0.0005247248,2.66012e-7,0.00002584126,0.4955243,0.440485,0.00007418705,0.03403929,0.00283023],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8619554,0.002622992,0.1284479,0.001369703,0.001904339,0.001464735,0.0002443067,0.00196888,0.00002171492],"genre_scores_gemma":[0.9832076,0.0001290413,0.01505574,0.0005546465,0.0007294724,0.0001807241,0.000001380868,0.0001394836,0.000001886277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1212522,"threshold_uncertainty_score":0.9997401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983375425951787,"score_gpt":0.2413345182443785,"score_spread":0.2215007639848606,"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."}}