{"id":"W1995447062","doi":"10.3390/jlpea3020114","title":"Synergistic Sensory Platform: Robotic Nurse","year":2013,"lang":"en","type":"article","venue":"Journal of Low Power Electronics and Applications","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"CrossWing (Canada); Wilfrid Laurier University","funders":"","keywords":"Flexibility (engineering); Operability; Computer science; Embedded system; Reliability (semiconductor); Robot; Electronics; Real-time computing; Simulation; Artificial intelligence; Engineering; Power (physics); Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000851834,0.0001432837,0.0002068392,0.0000689173,0.0001745344,0.00008011457,0.0002195549,0.00008943921,0.0008779063],"category_scores_gemma":[0.00001466983,0.0001264517,0.00009250249,0.0001476974,0.00007548527,0.0001582915,0.00001651848,0.0003902876,0.00007207219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009261476,"about_ca_system_score_gemma":0.0001304868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006192211,"about_ca_topic_score_gemma":0.00000325785,"domain_scores_codex":[0.9989619,0.000005691434,0.0004073002,0.0001619148,0.0001700866,0.0002931398],"domain_scores_gemma":[0.9989821,0.0000953759,0.0002808356,0.000287852,0.0001745611,0.0001792935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002695836,0.0006509015,0.000443887,0.000096075,0.0002184863,0.000004246266,0.0001847324,0.0006844814,0.7492056,0.2371322,0.004939693,0.006412766],"study_design_scores_gemma":[0.003968632,0.0006627215,0.002756824,0.0002955704,0.0008469809,0.001194326,0.002613769,0.01135143,0.3088543,0.2161845,0.4492921,0.001978821],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8549963,0.00783073,0.08737561,0.003114355,0.0000869561,0.0006230568,0.00002704063,0.0001198394,0.0458261],"genre_scores_gemma":[0.99739,0.0004108714,0.0006682229,0.0001199795,0.0001579568,0.0001088648,0.000007508392,0.000022591,0.001114011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4443524,"threshold_uncertainty_score":0.9612458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005571449540342843,"score_gpt":0.2403963978168041,"score_spread":0.2348249482764612,"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."}}