{"id":"W4214878542","doi":"10.1186/s12898-017-0138-8","title":"BMC ecology image competition 2017: the winning images","year":2017,"lang":"en","type":"editorial","venue":"BMC Ecology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Beauty; Competition (biology); Ecology; Selection (genetic algorithm); Diversity (politics); Computer science; Biology; Sociology; Artificial intelligence; Art; Aesthetics","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007071865,0.0003620245,0.0004889179,0.00004456135,0.000921312,0.000164716,0.001252547,0.0009467455,0.09376235],"category_scores_gemma":[0.001400704,0.0002903348,0.0001981551,0.00006942799,0.001435131,0.0001955735,0.0008916162,0.0007368319,0.01482754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083412,"about_ca_system_score_gemma":0.0001392627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002708033,"about_ca_topic_score_gemma":0.0240226,"domain_scores_codex":[0.997536,0.0003231424,0.0003671844,0.0006799999,0.0003965741,0.0006971186],"domain_scores_gemma":[0.9972086,0.001186907,0.0005599455,0.000882016,0.00005443611,0.0001081203],"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":[0.00002954141,0.00006681405,0.01321292,0.00002885392,0.0000127828,0.00001683832,0.000035355,0.000005197577,0.0001846838,0.0001799606,0.9861957,0.00003128263],"study_design_scores_gemma":[0.0004949491,0.0001051249,0.1943468,0.000007892207,0.00005240884,0.00001175874,0.0002200485,0.00001441364,0.00003532359,0.0001695603,0.8042722,0.0002694538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.006887963,0.00008492835,0.0001267867,0.000734305,0.8355938,0.0006018204,0.0009453687,0.0001309758,0.154894],"genre_scores_gemma":[0.02026882,0.001230214,0.0009299777,0.0009414646,0.9186708,0.0008640738,0.00751127,0.0001973479,0.04938603],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1819235,"threshold_uncertainty_score":0.9999549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02557064224385422,"score_gpt":0.2851714579701199,"score_spread":0.2596008157262656,"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."}}