{"id":"W1545412296","doi":"","title":"Earth Science Education 5. Effective Industry Outreach. Two Leading Examples from the Mineral Industry","year":2002,"lang":"en","type":"article","venue":"Geoscience Canada","topic":"Geography Education and Pedagogy","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Teck (Canada)","funders":"","keywords":"Outreach; Library science; Political science; Documentation; Humanities; Art; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008829476,0.0001339153,0.0001144712,0.0001137594,0.002300962,0.0003269153,0.0009458242,0.0001424135,0.001119521],"category_scores_gemma":[0.0008532553,0.0001097114,0.00003406224,0.001599045,0.001646186,0.0004869156,0.00005927075,0.0006642334,0.00002566333],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003101784,"about_ca_system_score_gemma":0.007873703,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9783689,"about_ca_topic_score_gemma":0.9689218,"domain_scores_codex":[0.9976094,0.0002075454,0.0001640837,0.0004531218,0.0009236612,0.0006421753],"domain_scores_gemma":[0.9985932,0.0003505256,0.0001135236,0.0003379681,0.000207974,0.000396815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001946331,0.0001015726,0.8083729,0.000002342244,0.000007535948,0.000002677847,0.02251695,0.00004465369,0.0008218928,0.0116272,0.02872665,0.1277737],"study_design_scores_gemma":[0.000113059,0.00001402483,0.5709133,0.00002636161,0.00001019872,0.000002464125,0.03992343,0.00007855085,0.0001677774,0.0003053384,0.3882085,0.0002370161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9531341,0.0002233744,0.00001071943,0.009094136,0.002706022,0.0002750619,0.00002318691,0.00003185835,0.0345015],"genre_scores_gemma":[0.9869657,0.00001060202,0.0001489772,0.003115825,0.0006434265,0.00003357831,0.000003900676,0.000005235217,0.009072774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3594818,"threshold_uncertainty_score":0.9997936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03555400809884812,"score_gpt":0.3193803355844203,"score_spread":0.2838263274855722,"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."}}