{"id":"W4407410383","doi":"10.1139/facets-2024-0180","title":"An ensemble machine learning bioavailable strontium isoscape for Eastern Canada","year":2025,"lang":"en","type":"article","venue":"FACETS","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Université Laval; University of Ottawa; Carleton University; Natural Resources Canada","funders":"Natural Resources Canada; Leverhulme Trust; UK Research and Innovation; McGill University","keywords":"Strontium; Bioavailability; Computer science; Chemistry; Biology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0008914024,0.001049781,0.0005243294,0.001374079,0.0007360444,0.0007851368,0.001237626,0.0005580809,0.0008302219],"category_scores_gemma":[0.001311765,0.0002721209,0.001045061,0.001539789,0.0004228518,0.0004511281,0.0005959527,0.0006798513,0.0002737211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004132563,"about_ca_system_score_gemma":0.004802607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7713648,"about_ca_topic_score_gemma":0.8272957,"domain_scores_codex":[0.9997085,0.00002852757,0.000009213622,0.0001215567,0.00007193888,0.00006031442],"domain_scores_gemma":[0.9994428,0.00008870713,0.00002961718,0.00005068987,0.0003563055,0.00003186709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001965369,0.0001079569,0.06804565,0.00008900328,0.0002980533,0.0002001453,0.00009737693,0.7887933,0.003480946,0.0007439074,0.007200351,0.1307468],"study_design_scores_gemma":[0.00001671756,0.00001761792,0.01960308,0.00001059703,0.00005069224,0.00001858863,0.00006618352,0.9762115,0.001415474,0.0004547526,0.002109359,0.00002534006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8771243,0.001198625,0.09831589,0.0005522409,0.00009669654,0.0001397659,0.01257309,0.003623631,0.006375755],"genre_scores_gemma":[0.9238034,0.000288817,0.04874464,0.0001335526,0.00002225729,0.00006637073,0.02315358,0.0002448812,0.003542468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2286352,"threshold_uncertainty_score":0.4599633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006282628429666548,"score_gpt":0.2408598829116252,"score_spread":0.2345772544819587,"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."}}