{"id":"W6936708174","doi":"10.5880/pik.2018.005","title":"ISIMIP2a Simulation Data from Fisheries & Marine Ecosystems (Fish-MIP; global) Sector","year":2018,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia; Dalhousie University","funders":"","keywords":"Climate change; Climate model; Ecological forecasting; Impact assessment; Marine ecosystem; Set (abstract data type); Ecosystem; Earth system science; Global change; Simulation modeling","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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.001321766,0.001082142,0.001429319,0.0001545247,0.0003097756,0.002836267,0.009331159,0.0009977638,0.1610918],"category_scores_gemma":[0.001126719,0.001098158,0.0001195936,0.0006400724,0.0002284996,0.002132228,0.01224234,0.000572892,0.1355721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007012935,"about_ca_system_score_gemma":0.0006074605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.049399,"about_ca_topic_score_gemma":0.5910449,"domain_scores_codex":[0.9935502,0.000568271,0.001266961,0.002671616,0.001156268,0.0007867113],"domain_scores_gemma":[0.9879364,0.0004279335,0.001388916,0.009550412,0.000338523,0.0003577571],"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":[0.0004071226,0.0001916898,0.0004953041,0.00005993704,0.0004805946,0.00004363041,0.00003184368,0.0001244256,0.000008482903,6.518492e-8,0.9967065,0.001450344],"study_design_scores_gemma":[0.001171488,0.00006577356,0.0003750561,0.0003744852,0.000588754,0.0000117041,0.00002505045,0.001727445,0.00001244992,0.00003596228,0.9944089,0.001202912],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004584641,0.00005891393,0.00001494588,0.00006916888,0.002114837,0.002137167,0.9884,0.00001956438,0.002600782],"genre_scores_gemma":[0.00009850913,0.00002704823,0.003476215,0.0001041669,0.002459959,0.00004495049,0.9919462,0.0001835783,0.001659409],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5416459,"threshold_uncertainty_score":0.9991469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1420337465674135,"score_gpt":0.3680236781533668,"score_spread":0.2259899315859533,"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."}}