{"id":"W4394346346","doi":"10.6084/m9.figshare.13125170","title":"Herring Gull Abundance in parking lots with/without automobile vehicles","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Herring; Abundance (ecology); Fishery; Herring gull; Larus; Biology; Fish <Actinopterygii>","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":["insufficient_payload"],"category_scores_codex":[0.00009997452,0.0004609449,0.0005813782,0.0002611529,0.00006008534,0.0002074197,0.0008124367,0.0003578252,0.01350633],"category_scores_gemma":[0.0003510502,0.0004662261,0.00007341054,0.0005090874,0.00001021211,0.0001468744,0.000236782,0.001202937,0.008821263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106755,"about_ca_system_score_gemma":0.0001258832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001098385,"about_ca_topic_score_gemma":0.0008698121,"domain_scores_codex":[0.9977266,0.00007339648,0.0004053956,0.0005497489,0.0005826317,0.0006622386],"domain_scores_gemma":[0.9988186,0.0001776074,0.00009428496,0.0006840607,0.00005616634,0.0001692887],"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":[0.000008089565,0.000009349183,0.00009375708,0.00318155,0.00004466953,0.0003410189,0.00005129408,0.003952574,0.00001719856,4.23239e-8,0.9919362,0.0003642627],"study_design_scores_gemma":[0.000280063,0.00002971012,0.0006150133,0.01312293,0.000006475277,0.00002558049,0.00001382323,0.003659885,0.0001367083,6.534826e-7,0.9815941,0.0005149956],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009311217,0.0007837155,7.636264e-7,0.00000805256,0.0001596818,0.0005791298,0.9975685,0.0004340003,0.0003730122],"genre_scores_gemma":[0.004639217,0.0000178537,0.00004065162,0.00002997299,0.0005248724,0.0009092231,0.993652,0.0001361725,0.00005004955],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01034203,"threshold_uncertainty_score":0.9997789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03374838257597437,"score_gpt":0.2637709994506013,"score_spread":0.2300226168746269,"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."}}