{"id":"W4398775181","doi":"10.1186/s13750-024-00334-5","title":"Navigating the science policy interface: a co-created mind-map to support early career research contributions to policy-relevant evidence","year":2024,"lang":"en","type":"article","venue":"Environmental Evidence","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; McGill University","funders":"United Nations Development Programme; Global Environment Facility","keywords":"Interface (matter); Science policy; Mind map; Research policy; Political science; Psychology; Public relations; Sociology; Business; Public administration; Computer science; Mathematics education","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06925126,0.002036066,0.001471117,0.01559983,0.006912858,0.0311108,0.005428882,0.009633748,0.02101782],"category_scores_gemma":[0.1503446,0.001397047,0.003466148,0.008455336,0.01292076,0.03276144,0.0444039,0.008622621,0.00988181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007872378,"about_ca_system_score_gemma":0.02002895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001678941,"about_ca_topic_score_gemma":0.003981831,"domain_scores_codex":[0.9523035,0.03441523,0.003147655,0.00293856,0.005239624,0.001955351],"domain_scores_gemma":[0.7885798,0.1590735,0.005432144,0.01827753,0.01508847,0.01354853],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003686396,0.0004801605,0.005505939,0.006512035,0.0002837091,0.001419166,0.1776887,0.004635053,0.003497709,0.171377,0.1574474,0.4707845],"study_design_scores_gemma":[0.0001490458,0.0001378171,0.001189795,0.003479394,0.000138361,0.0005047044,0.03928054,0.003980204,0.001619941,0.2417937,0.7075092,0.0002172862],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03779193,0.007111443,0.6266165,0.1501442,0.006498528,0.004453018,0.004839241,0.01403444,0.1485108],"genre_scores_gemma":[0.1436322,0.002618996,0.8215915,0.00673675,0.0008177871,0.005395537,0.002958266,0.002321849,0.01392715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9307488,"threshold_uncertainty_score":0.36624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4693317648720658,"score_gpt":0.5902948753399004,"score_spread":0.1209631104678346,"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."}}