{"id":"W1971795420","doi":"10.1021/es991419w","title":"Mercury in the Soil-Plant-Deer-Predator Food Chain of a Temperate Forest in Slovenia","year":2000,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":184,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Capreolus; Roe deer; Mercury (programming language); Herbivore; Trophic level; Food chain; Bioindicator; Biomagnification; Methylmercury; Ecology; Biology; Environmental chemistry; Bioaccumulation; Chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007159197,0.0001719027,0.0002084708,0.0002588955,0.0001719376,0.00001487745,0.0008541958,0.0001023761,0.001481515],"category_scores_gemma":[0.00004613113,0.0001280769,0.00003470243,0.001418911,0.002844263,0.0003195833,0.0002485013,0.0002388233,0.0002983356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002332597,"about_ca_system_score_gemma":0.0000165067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00016348,"about_ca_topic_score_gemma":0.001042695,"domain_scores_codex":[0.9981709,0.00005357216,0.0003422127,0.0004171774,0.0004832425,0.0005329418],"domain_scores_gemma":[0.9994062,0.00003669592,0.0001005291,0.0003994586,0.000001029269,0.00005612936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001972073,0.0002467169,0.8127652,0.000002862866,0.000003957344,0.00001238784,0.002395191,0.0008208839,0.1646423,0.0003333287,0.0001426874,0.01861468],"study_design_scores_gemma":[0.0008031877,0.0004614258,0.9391165,0.00002547199,0.000007935107,0.00007234421,0.004106085,0.0004643291,0.04626532,0.002360506,0.005983287,0.00033364],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952627,0.0001040347,0.000007594424,0.001128848,0.00003740189,0.0003354226,0.00003111053,0.00002370798,0.003069186],"genre_scores_gemma":[0.9992946,0.0001843225,0.000105737,0.0002171296,0.000007366064,0.00005806436,0.000003999841,0.000007575635,0.0001212435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1263512,"threshold_uncertainty_score":0.9998694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008051788568146307,"score_gpt":0.2171097089030959,"score_spread":0.2090579203349495,"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."}}