{"id":"W2167306509","doi":"10.1039/c5fd00056d","title":"Fluorescent logic systems for sensing and molecular computation: structure–activity relationships in edge-detection","year":2015,"lang":"en","type":"article","venue":"Faraday Discussions","topic":"Molecular Sensors and Ion Detection","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computation; Scope (computer science); Enhanced Data Rates for GSM Evolution; Computer science; Artificial intelligence; Algorithm","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":[0.0001667883,0.0001518484,0.0001748482,0.0001013702,0.0002074745,0.00007010171,0.00004096193,0.0001669147,0.000005194492],"category_scores_gemma":[0.0002216404,0.0001194452,0.00005115021,0.0001679265,0.00003482254,0.0000897432,0.00003087683,0.0002586209,0.000002310017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001337208,"about_ca_system_score_gemma":0.00003120281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001186948,"about_ca_topic_score_gemma":0.0001006437,"domain_scores_codex":[0.9989815,0.0001159228,0.0002211219,0.0003074948,0.0001859976,0.0001879633],"domain_scores_gemma":[0.9994503,0.000050799,0.0001040216,0.0001730864,0.00008121003,0.0001406283],"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":[0.0001990679,0.0001455468,0.0009401891,0.0002715066,0.0000568651,0.00003805723,0.0009592134,0.03783022,0.9144204,0.001179921,0.0005696454,0.04338932],"study_design_scores_gemma":[0.002763404,0.0001285812,0.004580379,0.0002591155,0.00009461882,0.000181303,0.002354272,0.8248997,0.1523211,0.007089978,0.004597319,0.0007301732],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8367883,0.0003027316,0.1613306,0.0003840629,0.0004169862,0.0002896118,0.00003032722,0.00008748263,0.0003698852],"genre_scores_gemma":[0.9988775,0.000005755194,0.0008189338,0.00001370549,0.0000966082,0.00001259048,0.00003393135,0.00002279741,0.0001181481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7870695,"threshold_uncertainty_score":0.4870836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03645067770005395,"score_gpt":0.2652162777928738,"score_spread":0.2287656000928199,"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."}}