{"id":"W841289799","doi":"10.5821/dissertation-2117-95633","title":"Climate networks constructed by using information-theoretic measures and ordinal time-series analysis","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interdependence; Representation (politics); Mutual information; Climatology; Series (stratigraphy); Similarity (geometry); Climate change; Climate model; Computer science; Data mining; Artificial intelligence; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001588652,0.0004617812,0.0003878936,0.003879319,0.0004583915,0.002082756,0.0005660591,0.0004209087,0.001573942],"category_scores_gemma":[0.009801308,0.0002856745,0.000886116,0.002362022,0.001166178,0.00274774,0.00117552,0.0009436489,0.0001766121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001421731,"about_ca_system_score_gemma":0.0005735168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001992443,"about_ca_topic_score_gemma":0.001863915,"domain_scores_codex":[0.998942,0.0005397288,0.00008076318,0.0002001172,0.0001867291,0.00005076972],"domain_scores_gemma":[0.9947183,0.003575501,0.0008291234,0.0003244139,0.0004198961,0.0001329003],"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":[0.00005460755,0.00004094889,0.008639259,0.0002228888,0.0001215128,0.0001511646,0.0005789047,0.3572707,0.001783946,0.5539942,0.001051932,0.07608994],"study_design_scores_gemma":[0.00000509611,0.00002266912,0.002500638,0.00006574357,0.00002941886,0.00005163723,0.0001089599,0.7271429,0.00056234,0.2658736,0.003613665,0.00002342378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05511481,0.0006709809,0.9392801,0.0004166788,0.00003687961,0.00005828068,0.0005850728,0.0001264036,0.003710898],"genre_scores_gemma":[0.5889454,0.001600207,0.405202,0.00009895622,0.0001223356,0.0003234087,0.001581851,0.00007997939,0.002045914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003879319,"threshold_uncertainty_score":0.01031548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218489364193574,"score_gpt":0.2095745918070225,"score_spread":0.1973896981650868,"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."}}