{"id":"W3127440096","doi":"10.1038/s41467-021-27274-9","title":"Analog programing of conducting-polymer dendritic interconnections and control of their morphology","year":2021,"lang":"en","type":"preprint","venue":"Nature Communications","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Biochip; Massively parallel; Neuromorphic engineering; Computer science; Materials science; Duty cycle; Memristor; Nanotechnology; Branching (polymer chemistry); Bridging (networking); Biological system; Artificial intelligence; Electronic engineering; Voltage; Artificial neural network; Electrical engineering; Parallel computing; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004418043,0.0001070013,0.00005880739,0.00009207902,0.00009989077,0.0002023494,0.0002681774,0.0001225242,0.002114742],"category_scores_gemma":[0.0002166469,0.00005604568,0.00006287523,0.0001298663,0.0001774459,0.0002263612,0.0001117303,0.0001314007,0.0002605096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001249847,"about_ca_system_score_gemma":0.0000799743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001052719,"about_ca_topic_score_gemma":0.0002343571,"domain_scores_codex":[0.9999654,0.000003155471,0.000001561068,0.00001110739,0.00001288326,0.000005923742],"domain_scores_gemma":[0.999927,0.00002472041,0.00001444,0.00001660928,0.000009217079,0.000008065273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006126599,0.0000482554,0.0004510671,0.00007131544,0.000005242245,0.0001161887,0.00004741399,0.003990212,0.9578055,0.004128948,0.0004337304,0.03284086],"study_design_scores_gemma":[0.00002031691,0.0001633413,0.002277738,0.000007314155,0.000009675093,0.0002587749,0.00002736354,0.07948136,0.9068412,0.003529118,0.007374655,0.000009205548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8756207,0.0004049149,0.1041029,0.000265694,0.0001105143,0.00005050209,0.000253803,0.00105345,0.01813756],"genre_scores_gemma":[0.9915209,0.0001117688,0.006285203,0.0000198782,0.000006730911,0.00001218644,0.00004089641,0.00002587128,0.001976504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002114742,"threshold_uncertainty_score":0.007074535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0390523434808068,"score_gpt":0.3013048039895927,"score_spread":0.2622524605087859,"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."}}