{"id":"W2016912832","doi":"10.1155/2008/369601","title":"The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science","year":2008,"lang":"en","type":"article","venue":"International Journal of Plant Genomics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; BC Cancer Agency; University of British Columbia","funders":"Wageningen University and Research; Consortium of International Agricultural Research Centers; Centre de Coopération Internationale en Recherche Agronomique pour le Développement","keywords":"Interoperability; Workbench; Computer science; Suite; Ontology; Middleware (distributed applications); Domain (mathematical analysis); Implementation; Data science; World Wide Web; Data access; Database; Software engineering; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.0005381633,0.00007656028,0.00008223551,0.00004470797,0.000299603,0.00006675123,0.0002863272,0.00003420702,5.577917e-7],"category_scores_gemma":[0.0001220169,0.00005435371,0.00005142391,0.0000228204,0.0002039205,0.000003368247,0.00008507991,0.00004971465,1.718462e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004544232,"about_ca_system_score_gemma":0.0003920191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000385666,"about_ca_topic_score_gemma":0.0000366929,"domain_scores_codex":[0.9992434,0.000006984259,0.0002347797,0.0001154309,0.0002489062,0.0001504758],"domain_scores_gemma":[0.9989833,0.00002293083,0.0001740522,0.00007467098,0.0006925742,0.00005245786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005318405,0.00007472611,0.00186716,0.000007432939,0.0004004083,0.0000208336,0.0008051629,0.0004886506,0.9625646,0.002468008,0.002853482,0.02791773],"study_design_scores_gemma":[0.003291739,0.001907019,0.007510104,0.00003786735,0.00007332892,0.002758467,0.00062543,0.004441632,0.1576787,0.002340038,0.8188384,0.0004972888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930972,0.003103289,0.002271807,0.0005034335,0.0007366405,0.0001149594,0.0001105954,6.706097e-7,0.00006140184],"genre_scores_gemma":[0.9877732,0.009402964,0.001873901,0.00006081133,0.0008249269,0.000004823494,0.00001263562,0.000007178561,0.00003949741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8159849,"threshold_uncertainty_score":0.2304334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0347159698769722,"score_gpt":0.2768127674649806,"score_spread":0.2420967975880084,"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."}}