{"id":"W7126593503","doi":"","title":"Local perspectives on regional adaptation: Vertical, horizontal, and temporal coordination on New York?s Lake Ontario Shoreline","year":2022,"lang":"en","type":"report","venue":"eCommons (Cornell University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shore; Watershed; Water resources; State (computer science); Hydrology (agriculture)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005348889,0.0008564841,0.0008999755,0.001948926,0.0006942959,0.0001185117,0.0006492467,0.0005588451,0.002584805],"category_scores_gemma":[0.0001323917,0.001041759,0.0004173693,0.001446444,0.0005015737,0.0003217336,0.0003759398,0.002206622,0.0005622242],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009199857,"about_ca_system_score_gemma":0.004673993,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03168454,"about_ca_topic_score_gemma":0.5483273,"domain_scores_codex":[0.9955916,0.0003597357,0.000510024,0.001729569,0.001193809,0.0006152469],"domain_scores_gemma":[0.9973221,0.0003344853,0.000411882,0.0009158968,0.0004355965,0.0005800527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003161408,0.002000435,0.009286364,0.00006482346,0.0009257558,0.002000866,0.004199634,0.01968441,0.000004630463,0.02904172,0.9282814,0.001348583],"study_design_scores_gemma":[0.00234314,0.002388805,0.01025646,0.0002023206,0.0005380537,0.0001499016,0.009351184,0.001861545,0.000004056188,0.0003527019,0.9713185,0.00123329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3584975,0.001839939,0.006493627,0.002424135,0.004367594,0.004487112,0.002882967,0.004230596,0.6147766],"genre_scores_gemma":[0.8999591,0.000239712,0.0002123218,0.0000692582,0.0005250894,0.000005702779,0.003067341,0.0004081111,0.09551328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5414616,"threshold_uncertainty_score":0.9992033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09414297580399522,"score_gpt":0.2374743736421923,"score_spread":0.1433313978381971,"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."}}