{"id":"W6929716929","doi":"10.5061/dryad.b75j7","title":"Data from: Energy benefits and emergent space use patterns of an empirically parameterized model of memory-based patch selection","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Université Laval","funders":"","keywords":"Foraging; Optimal foraging theory; Selection (genetic algorithm); Parameterized complexity; Quality (philosophy); Energy (signal processing); Space (punctuation); Home range","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004807058,0.0003437138,0.0003681958,0.0003131372,0.0003006184,0.0005664652,0.001106087,0.000756785,0.004122559],"category_scores_gemma":[0.002693685,0.000215568,0.0004940336,0.0004565872,0.0004725705,0.0004745753,0.0003087923,0.000509308,0.0003485202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001955432,"about_ca_system_score_gemma":0.0008470595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2304721,"about_ca_topic_score_gemma":0.2139923,"domain_scores_codex":[0.9998926,0.00002933525,0.000006947535,0.00003309954,0.00001639468,0.00002162811],"domain_scores_gemma":[0.9991254,0.000431347,0.0001114337,0.0001127389,0.0001560731,0.00006296767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001713991,0.0000724218,0.04299936,0.00008013933,0.00007116899,0.0001442978,0.0001238527,0.9431005,0.001183847,0.005347877,0.001836836,0.004868388],"study_design_scores_gemma":[0.00007774987,0.00003611015,0.02105215,0.00001915072,0.0000259355,0.00005263208,0.00006030771,0.973978,0.0004484812,0.003036916,0.001190401,0.00002222461],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9865875,0.0001215073,0.007147081,0.0002772748,0.000008156532,0.00003139106,0.002608724,0.0000820422,0.003136406],"genre_scores_gemma":[0.9954175,0.00005642233,0.001993447,0.00003097851,0.000002394177,0.00003455168,0.001373758,0.00001864562,0.001072299],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.2304721,"threshold_uncertainty_score":0.4582612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07861159694324106,"score_gpt":0.2931341412865213,"score_spread":0.2145225443432803,"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."}}