{"id":"W4400524162","doi":"10.2139/ssrn.4884727","title":"Geographic gradients in species interactions: from latitudinal patterns to ecological mechanisms","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Ecology; Geography; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0008642643,0.0002166457,0.0003901642,0.001281621,0.0003151402,0.001764167,0.0002295244,0.0004792698,0.004564213],"category_scores_gemma":[0.003715441,0.0003016979,0.0002902677,0.002480719,0.00104371,0.00151134,0.0007332807,0.0004478355,0.0003321207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002467085,"about_ca_system_score_gemma":0.0001933219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002919708,"about_ca_topic_score_gemma":0.004059395,"domain_scores_codex":[0.9997851,0.00009046304,0.00001450364,0.00005466684,0.00002792282,0.00002733374],"domain_scores_gemma":[0.9973266,0.001773114,0.0004403941,0.0001668674,0.0001290518,0.0001639969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003219941,0.0001247044,0.8074382,0.0004911711,0.0008684151,0.0003090312,0.002228444,0.01601713,0.006237815,0.06431891,0.003473907,0.09817023],"study_design_scores_gemma":[0.00002411298,0.00004762147,0.9416725,0.00004522314,0.0001115879,0.0001563367,0.0008153393,0.006110359,0.0002654254,0.04879287,0.00193695,0.00002166117],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9814673,0.002712903,0.007539371,0.001039229,0.00003896017,0.000006745824,0.0005702531,0.00006014368,0.006565091],"genre_scores_gemma":[0.9965366,0.001124016,0.00114541,0.0000728231,0.00005382385,0.000007015894,0.0001998754,0.00002351771,0.0008369735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004564213,"threshold_uncertainty_score":0.01526886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02237581766903541,"score_gpt":0.2635159713783047,"score_spread":0.2411401537092693,"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."}}