{"id":"W4417001186","doi":"10.2139/ssrn.5823182","title":"Policy Paper from EcoLAWgy at the Eleventh Session of the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), agenda item 9.2 on the Enhancement of the MLS&lt;br&gt;","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; International Institute for Sustainable Development","funders":"","keywords":"Session (web analytics); Eleventh; Agriculture; Treaty; Genetic resources","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004679801,0.0001469113,0.0001202832,0.00002264449,0.000420985,0.00003594319,0.0008311121,0.00005424075,0.0002556349],"category_scores_gemma":[0.0001116018,0.00005671937,0.0001443703,0.0001202984,0.0001606771,0.00004717992,0.0003073508,0.000430409,0.000004788827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009541693,"about_ca_system_score_gemma":0.0001290914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003032486,"about_ca_topic_score_gemma":0.006481257,"domain_scores_codex":[0.9983712,0.0001594948,0.0002775965,0.0001950918,0.0005580335,0.0004385492],"domain_scores_gemma":[0.9990562,0.0003812441,0.0002773763,0.000240931,0.00002517237,0.00001913474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001611201,0.001026743,0.03859125,0.00002837101,0.002026654,0.000001525893,0.004364058,0.002925013,0.5180721,0.3820535,0.02280165,0.02649798],"study_design_scores_gemma":[0.002108371,0.001317649,0.3870819,0.0005449387,0.000210959,0.00007179447,0.001650749,0.0005870173,0.286447,0.2222625,0.09736784,0.0003493175],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799513,0.0003903671,0.00003225585,0.01432747,0.0001817037,0.0003769226,0.0001005606,0.000003177092,0.004636293],"genre_scores_gemma":[0.9917173,0.0004804128,0.00001451307,0.0009536974,0.0001413611,0.00002556313,0.000004479196,0.00000826763,0.006654421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3484906,"threshold_uncertainty_score":0.3616693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004551410997494409,"score_gpt":0.2143967988445579,"score_spread":0.2098453878470635,"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."}}