{"id":"W1799930692","doi":"10.1016/s0422-9894(03)80137-x","title":"Chapter 20 Space-time transfer function models of beach and shoreline data for medium-term shoreline monitoring programs","year":2003,"lang":"en","type":"book-chapter","venue":"Elsevier oceanography series","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Shore; Term (time); Sampling (signal processing); Spacetime; Temporal scales; Grid; Space (punctuation); Spatial analysis; Geology; Geography; Computer science; Oceanography; Remote sensing; Ecology; Geodesy; Physics; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003721997,0.0006193445,0.0007840473,0.0003051296,0.0001672635,0.00008646226,0.0004282612,0.0003221155,0.0003800011],"category_scores_gemma":[0.000008717852,0.0005268641,0.0002804706,0.0001081001,0.0004014874,0.0007475101,0.00008458764,0.000324992,0.000003717279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002981464,"about_ca_system_score_gemma":0.0000380546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001764209,"about_ca_topic_score_gemma":0.0009493555,"domain_scores_codex":[0.9976431,0.00001928552,0.0006627973,0.0008083872,0.0004342551,0.0004321643],"domain_scores_gemma":[0.9986428,0.00006475903,0.0001599581,0.0007286078,0.0001922557,0.0002116458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008377679,0.00004992254,0.01386272,0.0008097855,0.0005785743,0.000009814705,0.0002336024,0.0001635988,0.00001296164,0.003414433,0.0003648995,0.9796619],"study_design_scores_gemma":[0.001158782,0.002339353,0.001723168,0.0008713987,0.001385764,0.00004540352,0.000121696,0.01109242,0.00002031057,0.03228676,0.9471821,0.001772893],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03827805,0.1951297,0.02546763,0.004166267,0.01383404,0.02116784,0.0706495,0.001595124,0.6297118],"genre_scores_gemma":[0.08277773,0.09587383,0.03565617,0.0004891686,0.005536955,0.00007560712,0.1970719,0.0005728032,0.5819458],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.977889,"threshold_uncertainty_score":0.9997183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02734048126863583,"score_gpt":0.2120267145379425,"score_spread":0.1846862332693066,"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."}}