{"id":"W3151295882","doi":"10.29173/iasl7822","title":"Building Interest in Agricultural Research Through User Education Activities","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Information Retrieval and Data Mining","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Agency (philosophy); Indonesian; Agricultural education; Field (mathematics); Business; Agricultural communication; Funding Agency; Knowledge management; Public relations; Economic growth; Engineering; Political science; Computer science; Sociology; Geography; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004855731,0.0001326878,0.0001496153,0.0001684445,0.0001852347,0.001057604,0.0007041463,0.00008903071,0.00003448799],"category_scores_gemma":[0.0003824962,0.0001127896,0.0000318536,0.001154146,0.00007202601,0.006816759,0.0006516197,0.0004320423,0.00005193934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009776117,"about_ca_system_score_gemma":0.0004810285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006780274,"about_ca_topic_score_gemma":0.00001757758,"domain_scores_codex":[0.9985863,0.00002864036,0.0002822427,0.0003615977,0.0003435789,0.0003976664],"domain_scores_gemma":[0.9981717,0.00007750815,0.00008525922,0.0001390445,0.00145514,0.00007136104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001188823,0.0001114984,0.001229679,0.0000959713,0.00000793808,0.000005620779,0.1557691,0.0000010445,0.004543952,0.7977806,0.00631929,0.03412332],"study_design_scores_gemma":[0.000860585,0.0003122055,0.03442713,0.001344759,0.000008004536,0.0003147445,0.6096503,0.00286726,0.1876419,0.06729866,0.09408382,0.001190633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975242,0.00007215546,0.008735087,0.001822984,0.0002998664,0.0001317612,0.000007294451,0.00009178499,0.01359705],"genre_scores_gemma":[0.9777882,0.00002438275,0.02079717,0.0002832053,0.00009796872,0.00003174596,0.00001121767,0.000004361739,0.0009617392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.730482,"threshold_uncertainty_score":0.9999794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013948748897259,"score_gpt":0.3529482636364138,"score_spread":0.2515533887466879,"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."}}