{"id":"W2976797453","doi":"10.29169/1927-5129.2019.15.02","title":"Basic Ideas of Information Thermodynamics","year":2019,"lang":"en","type":"article","venue":"Journal of Basic & Applied Sciences","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Carnot cycle; Thermodynamic system; Fundamental thermodynamic relation; Thermodynamics; Laws of thermodynamics; Entropy (arrow of time); Statistical physics; Second law of thermodynamics; Mathematics; Thermodynamic process; Information theory; Thermodynamic equilibrium; Maximum entropy thermodynamics; Gibbs free energy; Thermodynamic free energy; Non-equilibrium thermodynamics; Physics; Binary entropy function; Principle of maximum entropy; Material properties","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007742244,0.00007759161,0.0001721657,0.000152652,0.00009019657,0.0001158882,0.001138382,0.00003061084,0.00001888675],"category_scores_gemma":[0.000008745093,0.00005457479,0.00007162396,0.0007283353,0.0001081749,0.001045635,0.00009527085,0.0001283353,0.00003439187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001884157,"about_ca_system_score_gemma":0.000141559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000303002,"about_ca_topic_score_gemma":9.753489e-7,"domain_scores_codex":[0.9987683,0.00001588263,0.000446871,0.0001039742,0.0005073142,0.0001576809],"domain_scores_gemma":[0.9988605,0.0001059442,0.0006409177,0.0002158837,0.0001166934,0.00006005281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001286426,0.00006324462,0.0009924724,0.00002112036,0.00001450487,7.190171e-7,0.000614382,0.01303095,0.01703908,0.8635438,0.0007489193,0.1039179],"study_design_scores_gemma":[0.002625315,0.001525114,0.04755674,0.0002651029,0.00005788833,0.0002529084,0.001705925,0.5276292,0.02474737,0.3688569,0.02376031,0.001017176],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8093275,0.00006586157,0.1665191,0.001042432,0.0003806567,0.0001808057,0.000001256188,0.00001731755,0.02246503],"genre_scores_gemma":[0.9878914,0.00002001257,0.0117228,0.0002944841,0.00004754927,0.000001863416,2.292478e-7,0.000001818778,0.00001979169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5145983,"threshold_uncertainty_score":0.2225495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009390957943228391,"score_gpt":0.2291187806489016,"score_spread":0.2197278227056732,"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."}}