{"id":"W7165779964","doi":"10.17605/osf.io/n8sqx","title":"Data and Code for \"In the Belly of the Beast: How Dietary Changes and Preexisting Invasive Prey may have Promoted the Success of a Novel Invasive Amphibian\"","year":2025,"lang":"","type":"article","venue":"Open Science Framework","topic":"Amphibian and Reptile Biology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Predation; Code (set theory); Population; Composition (language); Foraging","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.009857109,0.001039023,0.00101117,0.0049399,0.001118123,0.002119467,0.001917741,0.00151374,0.08300636],"category_scores_gemma":[0.07569242,0.0009393279,0.002712969,0.005661859,0.001697719,0.001975885,0.003516163,0.002419737,0.01840569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001296898,"about_ca_system_score_gemma":0.009985871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02252328,"about_ca_topic_score_gemma":0.04200281,"domain_scores_codex":[0.9952494,0.001245851,0.001023505,0.001039595,0.0009615197,0.0004800817],"domain_scores_gemma":[0.9434518,0.03962803,0.005306789,0.005409349,0.00518235,0.001021754],"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":[0.0007035394,0.00006040794,0.02894367,0.0114106,0.001074891,0.000517942,0.001978243,0.001939164,0.002968007,0.01538934,0.8973058,0.03770833],"study_design_scores_gemma":[0.0006010035,0.000122776,0.071184,0.003130776,0.001024298,0.0006139439,0.0006943129,0.004324499,0.00467495,0.01800339,0.8953374,0.0002886848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01219062,0.0005575567,0.0290499,0.004421973,0.001410329,0.0006539476,0.9160987,0.02553381,0.0100831],"genre_scores_gemma":[0.1716298,0.00134195,0.2578943,0.003988341,0.0003552723,0.008130848,0.500972,0.03702874,0.01865867],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9980823,"threshold_uncertainty_score":0.2776839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08159807584063274,"score_gpt":0.3366173484465887,"score_spread":0.255019272605956,"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."}}