Kajian Aspek Populasi Menggunakan Model Pertumbuhan Allometri Spesies Kerang Kapah di Pantai Binalatung Kota Tarakan
Bibliographic record
Abstract
The research goal was to compare the shells types of Kapah (Meretrix meretrix; M. lyrata; Geloniacoaxans) that found in the Coast Binalatung area, Tarakan and to assess the growth of shellfishallometri. Sampling is done by making a transect along the coast Binalatung as much as 12 transects.Each transect arranged lengthwise along the beach with 25 meters of each transect. Sampling wascarried out in the absence of repetition with an area of 25 x 25 meters transect. Sampling was done byusing tools such as Kapah’ rakes. The result showed the M. meretrix constistes of 63 % of Kapah’spopulation while M. lyrata and G. coaxans represent 27 % and 10 % respectively. Growth comparisonbetween shell length and weight was considered as positive allometri while comparison between thickshells and weight of shellfish Kapah was allometri negative.Keywords: shellfish kapah, allometri growth, Binalatung, Tarakan
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".