{"id":"W6939479332","doi":"10.6073/pasta/8563e8cc8b4434e48fa00e89395b2232","title":"North Temperate Lakes LTER: Crayfish Abundance 1981 - current","year":2022,"lang":"en","type":"dataset","venue":"Environmental Data Initiative","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crayfish; Minnow; Abundance (ecology); Predation; Trout; Temperate climate; Rainbow trout","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":[],"consensus_categories":[],"category_scores_codex":[0.0001293794,0.0004639717,0.0002480714,0.001663922,0.0003562764,0.0003663794,0.0004026491,0.000164953,0.03855946],"category_scores_gemma":[0.0003298221,0.0002032449,0.000221813,0.001810012,0.00009479342,0.0004415489,0.0005034491,0.0002247238,0.01256187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008955465,"about_ca_system_score_gemma":0.0006044869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1645915,"about_ca_topic_score_gemma":0.4773068,"domain_scores_codex":[0.999858,0.000006017775,0.00001676597,0.00003761903,0.0000569269,0.0000245024],"domain_scores_gemma":[0.9996177,0.00001116584,0.0001128497,0.00002793199,0.0001747125,0.00005566426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000623248,0.0001904619,0.5593277,0.000879463,0.0001204995,0.0002556246,0.00106148,0.0003993964,0.006298846,0.0002505826,0.3427252,0.08786738],"study_design_scores_gemma":[0.00001424332,0.00001977158,0.9613069,0.00002017266,0.00000805025,0.00003473672,0.0001024061,0.00009951018,0.0002120334,0.00001199126,0.03816579,0.000004388632],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3691612,0.0007717076,0.0006639314,0.0002667319,0.0001130483,0.0004857387,0.5610448,0.0009588096,0.06653412],"genre_scores_gemma":[0.378518,0.0006989516,0.00324045,0.0003289651,0.00009753931,0.00108221,0.511413,0.000208973,0.1044118],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1645915,"threshold_uncertainty_score":0.3272671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05995881033557916,"score_gpt":0.2909085992158314,"score_spread":0.2309497888802522,"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."}}